Dataset Information

Contributing Factors for Pediatric Ambulatory Diagnostic Process Errors: Project RedDE.

ABSTRACT: Background:Pediatric ambulatory diagnostic errors (DEs) occur frequently. We used root cause analyses (RCAs) to identify their failure points and contributing factors. Methods:Thirty-one practices were enrolled in a national QI collaborative to reduce 3 DEs occurring at different stages of the diagnostic process: missed adolescent depression, missed elevated blood pressure (BP), and missed actionable laboratory values. Practices were encouraged to perform monthly "mini-RCAs" to identify failure points and prioritize interventions. Information related to process steps involved, specific contributing factors, and recommended interventions were reported monthly. Data were analyzed using descriptive statistics and Pareto charts. Results:Twenty-eight (90%) practices submitted 184 mini-RCAs. The median number of mini-RCAs submitted was 6 (interquartile range, 2-9). For missed adolescent depression, the process step most commonly identified was the failure to screen (68%). For missed elevated BP, it was the failure to recognize (36%) and act on (28%) abnormal BP. For missed actionable laboratories, failure to notify families (23%) and document actions on (19%) abnormal results were the process steps most commonly identified. Top contributing factors to missed adolescent depression included patient volume (16%) and inadequate staffing (13%). Top contributing factors to missed elevated BP included patient volume (12%), clinic milieu (9%), and electronic health records (EHRs) (8%). Top contributing factors to missed actionable laboratories included written communication (13%), EHR (9%), and provider knowledge (8%). Recommended interventions were similar across errors. Conclusions:EHR-based interventions, standardization of processes, and cross-training may help decrease DEs in the pediatric ambulatory setting. Mini-RCAs are useful tools to identify their contributing factors and interventions.

SUBMITTER: Dadlez NM

PROVIDER: S-EPMC7297397 | biostudies-literature | 2020 May-Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Contributing Factors for Pediatric Ambulatory Diagnostic Process Errors: Project RedDE.

Dadlez Nina M NM Adelman Jason J Bundy David G DG Singh Hardeep H Applebaum Jo R JR Rinke Michael L ML

Pediatric quality & safety 20200512 3

<h4>Background</h4>Pediatric ambulatory diagnostic errors (DEs) occur frequently. We used root cause analyses (RCAs) to identify their failure points and contributing factors.<h4>Methods</h4>Thirty-one practices were enrolled in a national QI collaborative to reduce 3 DEs occurring at different stages of the diagnostic process: missed adolescent depression, missed elevated blood pressure (BP), and missed actionable laboratory values. Practices were encouraged to perform monthly "mini-RCAs" to id ...[more]

PMID: 32656467

Similar Datasets

Project description:ObjectivesTo summarize the literature on prevalence, impact, and contributing factors related to diagnostic error in the PICU.Data sourcesSearch of PubMed, EMBASE, and the Cochrane Library up to December 2019.Study selectionStudies on diagnostic error and the diagnostic process in pediatric critical care were included. Non-English studies with no translation, case reports/series, studies providing no information on diagnostic error, studies focused on non-PICU populations, and studies focused on a single condition/disease or a single diagnostic test/tool were excluded.Data extractionData on research design, objectives, study sample, and results pertaining to the prevalence, impact, and factors associated with diagnostic error were abstracted from each study.Data synthesisUsing independent tiered review, 396 abstracts were screened, and 17 studies (14 full-text, 3 abstracts) were ultimately included. Fifteen of 17 studies (88%) had an observational research design. Autopsy studies (autopsy rates were 20-47%) showed a 10-23% rate of missed major diagnoses; 5-16% of autopsy-discovered diagnostic errors had a potential adverse impact on survival and would have changed management. Retrospective record reviews reported varying rates of diagnostic error from 8% in a general PICU population to 12% among unexpected critical admissions and 21-25% of patients discussed at PICU morbidity and mortality conferences. Cardiovascular, infectious, congenital, and neurologic conditions were most commonly misdiagnosed. Systems factors (40-67%), cognitive factors (20-3%), and both systems and cognitive factors (40%) were associated with diagnostic error. Limited information was available on the impact of misdiagnosis.ConclusionsKnowledge of diagnostic errors in the PICU is limited. Future work to understand diagnostic errors should involve a balanced focus between studying the diagnosis of individual diseases and uncovering common system- and process-related determinants of diagnostic error.

Project description:BackgroundThe number of trained specialists world-wide is insufficient to serve all children with pediatric rheumatologic disorders, even in the countries with robust medical resources. We evaluated the potential of diagnostic decision support software (DDSS) to alleviate this shortage by assessing the ability of such software to improve the diagnostic accuracy of non-specialists.MethodsUsing vignettes of actual clinical cases, clinician testers generated a differential diagnosis before and after using diagnostic decision support software. The evaluation used the SimulConsult® DDSS tool, based on Bayesian pattern matching with temporal onset of each finding in each disease. The tool covered 5405 diseases (averaging 22 findings per disease). Rheumatology content in the database was developed using both primary references and textbooks. The frequency, timing, age of onset and age of disappearance of findings, as well as their incidence, treatability, and heritability were taken into account in order to guide diagnostic decision making. These capabilities allowed key information such as pertinent negatives and evolution over time to be used in the computations. Efficacy was measured by comparing whether the correct condition was included in the differential diagnosis generated by clinicians before using the software ("unaided"), versus after use of the DDSS ("aided").ResultsThe 26 clinicians demonstrated a significant reduction in diagnostic errors following introduction of the software, from 28% errors while unaided to 15% using decision support (p < 0.0001). Improvement was greatest for emergency medicine physicians (p = 0.013) and clinicians in practice for less than 10 years (p = 0.012). This error reduction occurred despite the fact that testers employed an "open book" approach to generate their initial lists of potential diagnoses, spending an average of 8.6 min using printed and electronic sources of medical information before using the diagnostic software.ConclusionsThese findings suggest that decision support can reduce diagnostic errors and improve use of relevant information by generalists. Such assistance could potentially help relieve the shortage of experts in pediatric rheumatology and similarly underserved specialties by improving generalists' ability to evaluate and diagnose patients presenting with musculoskeletal complaints.Trial registrationClinicalTrials.gov ID: NCT02205086.

Dataset Information

Contributing Factors for Pediatric Ambulatory Diagnostic Process Errors: Project RedDE.

Publications

Contributing Factors for Pediatric Ambulatory Diagnostic Process Errors: Project RedDE.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets