Elevating diagnostic skills with logical reasoning

Gilliam, Stephen

doi:10.1097/01.npr.0000554675.55073.5a

Cited by 5 publications

(4 citation statements)

References 5 publications

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“…The set of standardized language variables was finally analyzed to select from each extracted term one or maximum two standardized variables. This selection followed heuristic reasoning because it chose the most relevant standardized variables to represent the specific meaning of each term (Gilliam, 2019).…”

Section: Translation Of Terms To Taxonomiesmentioning

confidence: 99%

“…Taxonomic triangulation identifies diagnoses through the combination of data extracted from three different reference points (assessment, planning, and intervention) and with opposite logical relationship senses in the recognized linear process of nursing care. From assessment to diagnosis, we follow the established order, but from the criteria of outcomes and interventions towards the diagnosis the sense is inverse to the order (González-Aguña & Jiménez-Rodríguez, 2018).…”

Section: Introductionmentioning

confidence: 99%

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Nursing Diagnoses for Coronavirus Disease, COVID‐19: Identification by Taxonomic Triangulation

Aguña

Jiménez

Batalla

et al. 2020

Int J of Nursing Knowl

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To identify the nursing care problems related to the clinical process of disease by COVID-19. METHOD: The study applied the taxonomic triangulation technique on a clinical management guide to coronavirus disease, COVID-19, from the World Health Organization. The technique is divided into the phases: extraction of knowledge in natural language about assessment, planning and intervention, translation into standard language NOC and NIC, linking to NANDA-I diagnoses, triangulation looking for diagnostic matches in the three sets, and, finally, validation by a panel of experts from a hospital and a university. FINDINGS: The extraction identified 159 terms in natural language that were translated into 173 variables: 34 NOC for assessment, 19 NOC for planning, and 120 NIC for intervention. The relationships to NANDA-I diagnoses recorded 2,182 links and the triangulation returned 109 diagnoses, 54 of them for a critical situation. The panel of experts unanimously validated the 29 diagnoses with the highest number of links. CONCLUSION: Coronavirus disease, COVID-19, involves a complex situation with multiple associated care problems that can be identified using the taxonomic triangulation technique. IMPLICATIONS FOR NURSING PRACTICE:The links between taxonomies and the taxonomic triangulation technique are an important tool for generating knowledge. The results of this study may guide the diagnosis and treatment of coronavirus disease, COVID-19, as well as similar processes that occur with acute respiratory distress syndrome.

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Section: Translation Of Terms To Taxonomiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Nursing Diagnoses for Coronavirus Disease, COVID‐19: Identification by Taxonomic Triangulation

Aguña

Jiménez

Batalla

et al. 2020

Int J of Nursing Knowl

View full text Add to dashboard Cite

show abstract

“…Abductive reasoning, in which probable diagnoses can be generated from inductive and deductive reasoning, help focus the diagnostic possibilities to diagnoses of plausibility. That is, the designated diagnosis is the best explanation based on the data at hand (Gilliam, 2019;Soldati et al, 2017).…”

Section: Illness Scripts Metacognition and Data Acquisitionmentioning

confidence: 99%

Integrating strategies for improving diagnostic reasoning and error reduction

Nordick

2020

J Am Assoc Nurse Pract

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Errors of diagnostic reasoning contribute significantly to patient harm. Students, novice diagnosticians, and even experienced clinicians often have difficulty understanding or describing the processes of diagnostic reasoning. Inappropriate use of cognitive heuristics and poor logical reasoning by novice or experienced diagnosticians may result in missed or delayed diagnoses. Reduction of diagnostic errors through knowledge acquisition, self-reflection, and check lists has individually demonstrated some improvements in diagnostic reasoning. Implementing the diagnostic and reasoning tool (DaRT), a method of reasoning which integrates the evidence-based strategies of knowledge acquisition, metacognition, and logical reasoning skills throughout the patient encounter, results in improvement in diagnostic reasoning in advanced practice nurses. Use of the DaRT in one university setting resulted in significant improvement in advanced health assessment skills and diagnostic reasoning abilities as demonstrated by improvements of 28–55% end-of-program Health Education Systems Incorporated scores. Translation into practice settings may further support the use of this multiple-modality tool.

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“…When there is a failure in the diagnostic reasoning process and no accurate NDs are identified, inadequate interventions may be implemented and unexpected outcomes may occur, such as exposure to adverse events, prolonged hospital stay, and unnecessary readmissions (Bugs et al., 2018; Burt & Corbridge, 2018; Gilliam, 2019). Thus, diagnostic reasoning should be improved through educational strategies, such as case studies.…”

Section: Introductionmentioning

confidence: 99%

Development and validation of a case study to aid in the diagnostic reasoning of nursing students and nurses

Leandro

D’Agostino

Lopes

et al. 2023

Int J of Nursing Knowl

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PurposeThe aim of this study is to develop and validate a case study to aid in the diagnostic reasoning of nursing students and nurses.MethodsIt is a validation study using a case study based on Lunney's method including (1) content validation of the case study by nurse experts through the Delphi technique, (2) identification of nursing diagnoses (NDs) in the case, (3) evaluation of diagnostic accuracy, and (4) establishment of a priority diagnosis by nurse experts.FindingsThe case study was developed from the findings of a narrative literature review on the cues of the NDs with a prevalence > 50% in patients with peripheral arterial occlusive disease. Two rounds of expert evaluation were required to validate the case study. The experts identified 18 NDs with different degrees of accuracy. The highly accurate diagnoses most frequently identified by the experts were: Ineffective peripheral tissue perfusion (100%), impaired walking (83%), impaired comfort (50%), and chronic pain (50%). The diagnosis considered a priority by all experts was ineffective peripheral tissue perfusion.ConclusionsThe case study was developed and had its content validated. High‐accuracy diagnoses were identified, and a priority was determined.Implications for Nursing PracticeThe validated case study may be used by students and nurses to facilitate the development of diagnostic reasoning and critical thinking in practice, teaching or research.

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Elevating diagnostic skills with logical reasoning

Cited by 5 publications

References 5 publications

Nursing Diagnoses for Coronavirus Disease, COVID‐19: Identification by Taxonomic Triangulation

Nursing Diagnoses for Coronavirus Disease, COVID‐19: Identification by Taxonomic Triangulation

Integrating strategies for improving diagnostic reasoning and error reduction

Development and validation of a case study to aid in the diagnostic reasoning of nursing students and nurses

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