Assessing students with dyslexia and other reading difficulties through multiple diagnostic assessments.

This article aims to assist practitioners in understanding dyslexia and other reading difficulties and assessing students' learning needs. We describe the essential components of language and literacy, universal screening, diagnostic assessments, curriculum-based measurement and eligibility determination. We then introduce four diagnostic assessments as examples, including norm-referenced assessments (i.e. the Comprehensive Test of Phonological Processing second edition and the Woodcock-Johnson IV Tests of Achievement) and criterion-referenced assessments (i.e. the Gallistel-Ellis Test of Coding Skills and the Dynamic Indicators of Basic Early Literacy Skills). Finally, We use a makeup case as a concrete example to illustrate how multiple diagnostic assessments are recorded and how the results can be used to inform intervention and eligibility for special education services.

Delirium diagnostic tools in the postoperative setting: A scoping review protocol.

BACKGROUND: Delirium is an acute and fluctuating disturbance in attention, awareness, and cognition, commonly observed in hospital settings, particularly among older adults, critically ill and surgical patients. Delirium poses significant challenges in patient care, leading to increased morbidity, mortality, prolonged hospital stays, and functional decline. AIM: The aim of this review is to map existing evidence on delirium diagnostic tools suitable for use in patients treated surgically due to hip fracture, to inform clinical practice and enhance patient care protocols in the postoperative setting. METHOD: We will conduct a scoping review on delirium diagnostic tools used for adult patients in the postoperative setting according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). Eligibility criteria encompass all languages, publications dates, and study designs, with exception of case-reports. We will systematically search multiple databases and include unpublished trials, ensuring a comprehensive review based on a predefined protocol. RESULTS: Results will be presented descriptively, with supplementary tables and graphs. Studies will be grouped by design, surgical specialties, and diagnostic tools to identify potential variations. CONCLUSION: This scoping review will provide an overview of existing delirium diagnostic tools used in the postoperative setting and highlight knowledge-gaps to support future research. Due to the large number of patients affected by postoperative delirium, evidence mapping is much needed to facilitate evidence-based practice.

An exploratory Q-matrix estimation method based on sparse non-negative matrix factorization.

Cognitive diagnostic assessment (CDA) is widely used because it can provide refined diagnostic information. The Q-matrix is the basis of CDA, and can be specified by domain experts or by data-driven estimation methods based on observed response data. The data-driven Q-matrix estimation methods have become a research hotspot because of their objectivity, accuracy, and low calibration cost. However, most of the existing data-driven methods require known prior knowledge, such as initial Q-matrix, partial q-vector, or the number of attributes. Under the G-DINA model, we propose to estimate the number of attributes and Q-matrix elements simultaneously without any prior knowledge by the sparse non-negative matrix factorization (SNMF) method, which has the advantage of high scalability and universality. Simulation studies are carried out to investigate the performance of the SNMF. The results under a wide variety of simulation conditions indicate that the SNMF has good performance in the accuracy of attribute number and Q-matrix elements estimation. In addition, a set of real data is taken as an example to illustrate its application. Finally, we discuss the limitations of the current study and directions for future research.

Stated patient preferences for overnight at-home diagnostic assessment of sleep disorders.

PURPOSE: The diagnostic workup for assessment of sleep disorders commonly involves overnight testing to assess sleep patterns and pathological events. So far, little is known about preferences for provision of home sleep tests to patients with sleep disorders. This study aims to close this gap by eliciting preferences for home sleep testing using a discrete choice experiment (DCE). METHODS: A DCE with seven attributes of at-home sleep testing and three levels per attribute was developed using a fractional factorial design. Patients with and without previous sleep testing experience were recruited from two large sleep centers in Germany. Coefficients for attribute levels were calculated using a conditional logit model to estimate their influence on choice decisions and calculate the relative importance of each attribute. RESULTS: 305 patients (54.5 ± 13,1 years, 65.3% male) were enrolled, and 288 surveys with complete data included for analysis. Attributes with greatest relevance were Waiting time to discuss sleep study results; Waiting time to conduct sleep study, and Sleep quality during measurement. Of lowest importance was Diagnostic accuracy of sleep study, followed by Effort to apply sleep study device. Significant heterogeneity in choice behavior was found, including differences by gender, willingness-to-pay for sleep studies, and previous experience with sleep studies. Preferred location for conducting sleep testing was at-home in 50.7% and in-lab in 46.9%. CONCLUSIONS: Preferences and relative importance of home sleep test attributes vary among different subgroups. Considering those preferences can be important for clinicians and policymakers when designing care pathways and planning of testing policies for sleep disorders.

Clinical reappraisal of the composite international diagnostic interview version 3.3 in Qatar's National Mental Health Study.

OBJECTIVES: Lifetime DSM-5 diagnoses generated by the lay-administered Composite International Diagnostic Interview for DSM-5 (CIDI) in the World Mental Health Qatar (WMHQ) study were compared to diagnoses based on blinded clinician-administered reappraisal interviews. METHODS: Telephone follow-up interviews used the non-patient edition of the Structured Clinician Interview for DSM-5 (SCID) oversampling respondents who screened positive for five diagnoses in the CIDI: major depressive episode, mania/hypomania, panic disorder, generalized anxiety disorder, and obsessive-compulsive disorder. Concordance was also examined for a diagnoses of post-traumatic stress disorder based on a short-form versus full version of the PTSD Checklist for DSM-5 (PCL-5). RESULTS: Initial CIDI prevalence estimates differed significantly from the SCID for most diagnoses ( χ 1 2 ${\chi }_{1}^{2}$  = 6.6-31.4, p = 0.010 < 0.001), but recalibration reduced most of these differences and led to consistent increases in individual-level concordance (AU-ROC) from 0.53-0.76 to 0.67-0.81. Recalibration of the short-form PCL-5 removed an initially significant difference in PTSD prevalence with the full PCL-5 (from χ 1 2 ${\chi }_{1}^{2}$  = 610.5, p < 0.001 to χ 1 2 ${\chi }_{1}^{2}$  = 2.5, p = 0.110) while also increasing AU-ROC from 0.76 to 0.81. CONCLUSIONS: Recalibration resulted in valid diagnoses of common mental disorders in the Qatar National Mental Health Survey, but with inflated prevalence estimates for some disorders that need to be considered when interpreting results.

Cognitive diagnostic assessment: A Q-matrix constraint-based neural network method.

Cognitive diagnosis is a crucial element of intelligent education that aims to assess the proficiency of specific skills or traits in students at a refined level and provide insights into their strengths and weaknesses for personalized learning. Researchers have developed numerous cognitive diagnostic models. However, previous studies indicate that diagnostic accuracy can be significantly influenced by the appropriateness of the model and the sample size. Thus, designing a general model that can adapt to different assumptions and sample sizes remains a considerable challenge. Artificial neural networks have been proposed as a promising approach in some studies. In this paper, we propose a cognitive diagnosis model of a neural network constrained by a Q-matrix and named QNN. Specifically, we employ the Q-matrix to determine the connections between neurons and the width and depth of the neural network. Moreover, to reduce the human effort in the training algorithm, we designed a self-organizing map-based cognitive diagnosis training framework called SOM-NN, which enables the QNN to be trained unsupervised. Extensive experimental results on simulated and real datasets demonstrate that our approaches are effective in both accuracy and interpretability. Notably, under unsupervised conditions, our approach has significant advantages on small sample datasets with high levels of guessing and slipping, especially on the pattern-wise agreement rates. This work bridges the gap between psychometrics and machine learning and provides a realistic and implementable reference solution for classroom instructional assessment and the cold start of personalized and adaptive assessment systems.

Impact of the emotional development approach on psychotropic medication in adults with intellectual and developmental disabilities: a retrospective clinical analysis.

BACKGROUND: Compared with the general population, adults with an intellectual developmental disorder (IDD) are more likely to develop mental health problems and to receive high levels of psychotropic medication, particularly antipsychotics. The emotional development (ED) approach may help to better understand the nature of challenging behaviour (CB) and tailor treatment and support accordingly. The aim of this retrospective study was to investigate the impact of the ED approach on the prescription of psychotropic medication during inpatient psychiatric treatment. METHODS: The clinical data of 1758 patients were analysed within a retrospective study design over a period of 12 years. ED level was assessed (1) for the first time (INITIAL-SEO), (2) during a previous hospital stay (PAST-SEO) or (3) not at all (NO-SEO). The effects of the ED assessment and the respective intervention during the current admission on the number of psychotropics and the number and dosage of antipsychotics were analysed for the total sample, including those with CB, autism spectrum disorders and psychosis. Group differences were analysed by a chi-square test and a one-factorial analysis of variance. For analysing the impact of the application of the ED approach on psychotropic medication, a covariance model was applied. Changes between the subsamples were analysed by t-tests for dependent samples. RESULTS: The ED approach had a significant impact on reducing the overall amount of psychotropic medication and the dosage of antipsychotics in all patients with IDD. These effects were mainly attributable to those showing CB. In patients with autism spectrum disorders, the developmental approach reduced the number of antipsychotics. No effects could be observed in patients with psychosis; in this subsample, both the number and dosage of antipsychotics increased. CONCLUSIONS: The application of the ED approach in the current hospital stay reduced the number of psychotropic drugs and the number and dosage of antipsychotics, especially in those patients with IDD and CB, but also in those with autism spectrum disorders.

Identification of Psychosis Risk and Diagnosis of First-Episode Psychosis: Advice for Clinicians.

Early detection of psychotic-spectrum disorders among adolescents and young adults is crucial, as the initial years after psychotic symptom onset encompass a critical period in which psychosocial and pharmacological interventions are most effective. Moreover, clinicians and researchers in recent decades have thoroughly characterized psychosis-risk syndromes, in which youth are experiencing early warning signs indicative of heightened risk for developing a psychotic disorder. These insights have created opportunities for intervention even earlier in the illness course, ideally culminating in the prevention or mitigation of psychosis onset. However, identification and diagnosis of early signs of psychosis can be complex, as clinical presentations are heterogeneous, and psychotic symptoms exist on a continuum. When a young person presents to a clinic, it may be unclear whether they are experiencing common, mild psychotic-like symptoms, early warning signs of psychosis, overt psychotic symptoms, or symptoms better accounted for by a non-psychotic disorder. Therefore, the purpose of this review is to provide a framework for clinicians, including those who treat non-psychotic disorders and those in primary care settings, for guiding identification and diagnosis of early psychosis within the presenting clinic or via referral to a specialty clinic. We first provide descriptions and examples of first-episode psychosis (FEP) and psychosis-risk syndromes, as well as assessment tools used to diagnose these conditions. Next, we provide guidance as to the differential diagnosis of conditions which have phenotypic overlap with psychotic disorders, while considering the possibility of co-occurring symptoms in which case transdiagnostic treatments are encouraged. Finally, we conclude with an overview of early detection screening and outreach campaigns, which should be further optimized to reduce the duration of untreated psychosis among youth.

The Effect of Uncertainty Training on the Improvement of Diagnostic Ability in Chinese Medical Students.

Objective: To evaluate the effect of the uncertainty training on improvement of students' diagnostic ability. Methods: Data were collected on 70 fifth-year medical students enrolled in the Case Discussion courses on Obstetrics and Gynecology in the spring of 2020. Of these students, 36 were in the uncertainty training group and 34 in the control group. The effect of training was evaluated by cognitively diagnostic assessment which mapped exam questions to 4 attributes assessing clinical reasoning and basic science knowledge. Results: Uncertainty training was able to improve students' ability to use basic science concepts for inference and problem solving, and the ability to integrate complex clinical information to arrive at a diagnosis. But it could not improve students' ability on the basic recall of foundational concepts and the ability to use basic science concepts in clinical reasoning. Medical students could do well in integrating complex clinical information although they didn't recall basic science knowledge well. Conclusion: Uncertainty training could be used as an effective teaching method in Case Discussion course on Obstetrics and Gynecology. However, students still need to improve their basic knowledge besides the training.

A general nonparametric classification method for multiple strategies in cognitive diagnostic assessment.

Cognitive diagnosis models (CDMs) have been used as psychometric tools in educational assessments to estimate students' strengths and weaknesses in terms of cognitive skills learned and skills that need study. In practice, it is not uncommon that questions can often be solved using more than one strategy, which requires CDMs capable of accommodating multiple strategies. However, existing parametric multi-strategy CDMs need a large sample size to produce a reliable estimation of item parameters and examinees' proficiency class memberships, which obstructs their practical applications. This article proposes a general nonparametric multi-strategy classification method with promising classification accuracy in small samples for dichotomous response data. The method can accommodate different strategy selection approaches and different condensation rules. Simulation studies showed that the proposed method outperformed the parametric CDMs when sample sizes were small. A set of real data was analyzed as well to illustrate the application of the proposed method in practice.

Assessment of Autism Spectrum Disorder.

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by challenges in social interaction and communication and the presence of restricted interests and repetitive behaviors. The importance of early detection of ASD and subsequent early intervention is well documented. Efforts have been made over the years to clarify ASD diagnostic criteria and develop predictive, accurate screening tools and evidence-based, standardized diagnostic instruments to aid in the identification of ASD. In this article, we review the most recent changes in ASD diagnostic criteria in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision, summarize evidence-based instruments for ASD screening and diagnostic evaluations as well as the assessment of co-occurring conditions in ASD, the impact of COVID-19 on ASD assessment, and directions for future research in the field of ASD assessment.

The HAM-D6 through the lens of grief: Clinical considerations for administering the six-item Hamilton Depression Rating Scale in the context of bereavement.

OBJECTIVES: Diagnosing mental health challenges in bereavement is controversial; however, regardless of one's position on this matter, assessments of bereaved individuals continue to occur in clinical and research contexts. It is critical for evaluations to account for contextual factors that are unique to bereavement. This paper summarizes considerations for diagnosing depression in bereaved individuals, focusing on use of the six-item Hamilton Depression Rating Scale (HAM-D6). METHODS: Following a literature review of the Hamilton Depression Rating Scale (HAM-D) and various versions, we summarized decision rules we used in scoring the HAM-D6 in a study of parents bereaved by cancer. We expanded on existing scoring guidelines for each of the HAM-D6 items, including depressed mood, work and activities, general somatic symptoms, guilt, psychic anxiety, and psychomotor retardation, and illustrated clinical distinctions and probes for assessors to consider through case examples from our research with bereaved parents. RESULTS: Considerations for assessing depressive symptoms and behavior changes in the context of bereavement were summarized. Symptoms that may be diagnostic of depression in some populations may reflect other factors in the bereaved, such as a change in priorities, social expectations surrounding grief, or avoidance of grief activators. Nuanced factors are important for assessors to consider when administering the HAM-D6 to bereaved individuals. SIGNIFICANCE OF RESULTS: Our sharing of these considerations is not intended to promote diagnosis of depression in bereavement but to highlight the unique contextual factors that distinguish symptoms of depression from common experiences of grievers when applying an assessment tool such as the HAM-D6. While validated measures can be constraining, they can have clinical utility; they may increase standardization in research, help clinicians communicate with each other, advance the field more generally to understand the varying struggles bereaved individuals experience, and systemically facilitate access to services via managed care.

Diagnostic assessment of autism in adults - current considerations in neurodevelopmentally informed professional learning with reference to ADOS-2.

Services for the assessment and diagnosis of autism in adults have been widely criticized and there is an identified need for further research in this field. There is a call for diagnostic services to become more accessible, person-centered, neurodiversity affirming, and respectful. There is a need for workforce development which will increase capacity for diagnostic assessment and support for adults. ADOS-2 is a gold-standard diagnostic assessment tool for autism recommended in clinical guidelines. However, diagnostic procedures such as the ADOS-2 are rooted in the medical model and do not always sit comfortably alongside the neurodiversity paradigm or preferences of the autistic community. Training and educational materials need to account for the differences between these approaches and support clinicians to provide services which meet the needs of the adults they serve. The National Autism Implementation Team worked alongside ADOS-2 training providers to support clinicians in Scotland, to provide effective and respectful diagnostic assessment. The team engaged with clinicians who had attended ADOS training to identify areas of uncertainty or concern. Training materials were developed to support ADOS assessors to incorporate key principles including "nothing about us without us"; "difference not deficit"; "environment first"; "diagnosis matters," "language and mindsets matter"; and "a neurodevelopmental lens," to support the provision of neurodiversity affirming assessment practice. The National Autism Implementation Team also provided examples of actions which can be undertaken by clinicians to improve the assessment experience for those seeking a diagnosis. Training materials are based on research evidence, clinical experience, and the needs and wishes of autistic people.

Cognitive diagnostic assessment of EFL learners' listening barriers through incorrect responses.

English as Foreign Language (EFL) learners' cognitive processes have been a research focus in listening assessment. Most studies use correct responses as data, but undervalue the rich information of the incorrect answers or options (in the case of multiple choice questions, MCQ). However, the MCQ distractors are often intentionally designed to reveal learners' problems or barriers. In order to diagnose the EFL learners' listening barriers through incorrect responses, Cognitive Diagnostic Models (CDMs) for bugs were adopted, hence the name Bug-CDMs. First, five EFL listening barrier attributes were identified and two Bug Q-matrices were developed to comparatively analyze the learner's responses with different Bug-CDMs. The results revealed that Bug-GDINA was the optimal model, and the most prevalent barriers were semantic understanding and vocabulary recognition. These barriers confirmed both compensatory and non-compensatory relationships in causing listening comprehension failures. The study proved the feasibility of Bug-GDINA in diagnosing listening barriers from the incorrect responses. Limitations and suggestions for further research were also proposed.

Effects of the Pregnancy and Newborn Diagnostic Assessment (PANDA) App on Antenatal Care Quality in Burkina Faso: Protocol for a Cluster Randomized Controlled Trial.

BACKGROUND: The Pregnancy and Newborn Diagnostic Assessment (PANDA) system is a digital clinical decision support tool that can facilitate diagnosis and decision-making by health care personnel in antenatal care (ANC). Studies conducted in Madagascar and Burkina Faso showed that PANDA is a feasible system acceptable to various stakeholders. OBJECTIVE: This study primarily aims to evaluate the effects of the PANDA system on ANC quality at rural health facilities in Burkina Faso. The secondary objectives of this study are to test the effects of the PANDA system on women's satisfaction, women's knowledge on birth preparedness and complication readiness, maternal and child health service use, men's involvement in maternal health service utilization, and women's contraception use at 6 weeks postpartum. Further, we will identify the factors that hinder or promote such an app and contribute to cost-effectiveness analysis. METHODS: This is a randomized controlled trial implementing the PANDA system in 2 groups of health facilities (intervention and comparison groups) randomized using a matched-pair method. We included pregnant women who were <20 weeks pregnant during their first antenatal consultation in health facilities, and we followed up with them until their sixth week postpartum. Thirteen health centers were included, and 423 and 272 women were enrolled in the intervention and comparison groups, respectively. The primary outcome is a binary variable derived from the quality score, coded 1 (yes) for women with at least 75% of the total score and 0 if not. Data were collected electronically using tablets by directly interviewing the women and by extracting data from ANC registers, delivery registers, ANC cards, and health care records. The study procedures were standardized across all sites. We will compare unadjusted and adjusted primary outcome results (ANC quality scores) between the 2 study arms. We added a qualitative evaluation of the implementation of the PANDA system to identify barriers and catalysts. We also included an economic evaluation to determine whether the PANDA strategy is more cost-effective than the usual ANC strategy. RESULTS: The enrollment ran from July 2020 to January 2021 due to the COVID-19 pandemic. Data collection ended in September 2022. Data analyses started in January 2023, ended in June 2023, and the results are expected to be published in February 2024. CONCLUSIONS: The PANDA system is one of the most comprehensive apps for ANC because it has many features. However, the use of computerized systems for ANC is limited. Therefore, our trial will be beneficial for evaluating the intrinsic capacity of the PANDA system to improve the quality of care. By including qualitative research and economic evaluation, our findings will be significant because electronic consultation registries are expected to be used for maternal health care in the future in Burkina Faso. TRIAL REGISTRATION: Pan-African Clinical Trials Registry (PACTR) PACTR202009861550402; https://pactr.samrc.ac.za/TrialDisplay.aspx?TrialID=12374. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/37136.

Impact of Covid-19 on breast cancer stage at discovery, and time to treatment in Cote d'Or, France.

Due to the COVID-19 pandemic, and ensuing overcrowding in the French health system, management of patients with COVID-19 was given priority over that of patients with other pathologies, including chronic diseases. The aim of this study was to study the impact of COVID-19 on the stage of discovery of cancers diagnosed in the context of an organized breast cancer screening programme, as well as the impact on time to treatment. All women diagnosed with cancer in the Côte d'Or via organized breast cancer screening (first or second reading) from January 1, 2019 to December 31, 2020 were included in this study. Using data from pathological laboratories, clinical centers, and the breast and gynecological cancer registry of the Côte d'Or, France, we collected socio-demographic, clinical and treatment data on all patients. We compared data from the year 2019 (before-Covid) with the year 2020 (Covid). We did not observe a significant difference in the stage of breast cancer at discovery, or in time to treatment. However, the number of invasive cancers and the clinical size of in situ cancers both increased in 2020. Although these results are reassuring, continued monitoring is needed to determine the downstream effects of the pandemic.

Using a Generalized Logistic Regression Method to Detect Differential Item Functioning With Multiple Groups in Cognitive Diagnostic Tests.

Items with the presence of differential item functioning (DIF) will compromise the validity and fairness of a test. Studies have investigated the DIF effect in the context of cognitive diagnostic assessment (CDA), and some DIF detection methods have been proposed. Most of these methods are mainly designed to perform the presence of DIF between two groups; however, empirical situations may contain more than two groups. To date, only a handful of studies have detected the DIF effect with multiple groups in the CDA context. This study uses the generalized logistic regression (GLR) method to detect DIF items by using the estimated attribute profile as matching criteria. A simulation study is conducted to examine the performance of the two GLR methods, GLR-based Wald test (GLR-Wald) and GLR-based likelihood ratio test (GLR-LRT), in detecting the DIF items, the results based on the ordinary Wald test are also reported. Results show that (1) both GLR-Wald and GLR-LRT have more reasonable performance in controlling Type I error rates than the ordinary Wald test in most conditions; (2) the GLR method also produces higher empirical rejection rates than the ordinary Wald test in most conditions; and (3) using the estimated attribute profile as the matching criteria can produce similar Type I error rates and empirical rejection rates for GLR-Wald and GLR-LRT. A real data example is also analyzed to illustrate the application of these DIF detection methods in multiple groups.

Schizophrenia in autistic people with intellectual disabilities: Symptom manifestations and identification.

BACKGROUND: The assessment of schizophrenia in autistic people with intellectual disabilities is challenging. This study aimed to explore the identification of schizophrenia in this population. METHODS: Using data from a clinical multi-centre study, reported symptoms in 26 autistic individuals with intellectual disabilities diagnosed with co-occurring schizophrenia were explored. Scores on two checklists (Psychopathology in Autism Checklist [PAC], Aberrant Behaviour Checklist [ABC]) were compared with two comparison groups: autistic individuals with intellectual disabilities and other mental disorders (94), or no mental disorder (63). RESULTS: Reported symptoms of schizophrenia in this population met the formal diagnostic criteria. For PAC/ABC scales, only PAC psychosis differed for the schizophrenia group. Among participants with schizophrenia, two were diagnosed with additional mental disorders. Elevated scores for anxiety and depression were common. CONCLUSIONS: Emphasising core symptoms seems necessary when assessing co-occurring schizophrenia in autistic people with intellectual disabilities. The PAC may serve as a helpful screening tool.

Exploring the relationship between metacognitive awareness and Chinese EFL learners' listening skills.

Listening causes great difficulties for EFL learners and little is known concerning the contribution of EFL learners' metacognitive awareness to their listening performance and to their mastery of listening subskill. In the present study, the Metacognitive Awareness Listening Questionnaire (MALQ) and an in-house listening test were used to collect data from 567 Chinese EFL college students. The G-DINA package in R was adopted to identify students' mastery patterns of listening subskills. The correlations of test takers' MALQ results and their listening scores and listening subskills mastery probability were analyzed, respectively, to investigate how test participants' metacognitive awareness relates to their language proficiency and listening subskills. According to the study, learners' metacognitive awareness has a significant positive relationship with their listening performance at overall and subskills levels. The findings of the study provide additional evidence for using the MALQ as an instrument to interpret learners' metacognitive awareness of listening strategies. It is thus recommended that theorists and language teachers involve metacognitive awareness of strategies in listening instructions.

Assessing the Assessment-Developing and Deploying a Novel Tool for Evaluating Clinical Notes' Diagnostic Assessment Quality.

BACKGROUND: Ambulatory diagnostic errors are increasingly being recognized as an important quality and safety issue, and while measures of diagnostic quality have been sought, tools to evaluate diagnostic assessments in the medical record are lacking. OBJECTIVE: To develop and test a tool to measure diagnostic assessment note quality in primary care urgent encounters and identify common elements and areas for improvement in diagnostic assessment. DESIGN: Retrospective chart review of urgent care encounters at an urban academic setting. PARTICIPANTS: Primary care physicians. MAIN MEASURES: The Assessing the Assessment (ATA) instrument was evaluated for inter-rater reliability, internal consistency, and findings from its application to EHR notes. KEY RESULTS: ATA had reasonable performance characteristics (kappa 0.63, overall Cronbach's alpha 0.76). Variability in diagnostic assessment was seen in several domains. Two components of situational awareness tended to be well-documented ("Don't miss diagnoses" present in 84% of charts, red flag symptoms in 87%), while Psychosocial context was present only 18% of the time. CONCLUSIONS: The ATA tool is a promising framework for assessing and identifying areas for improvement in diagnostic assessments documented in clinical encounters.