Identifying diagnostic studies in MEDLINE: reducing the number needed to read.
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OBJECTIVES: The search filters in PubMed have become a cornerstone in information retrieval in evidence-based practice. However, the filter for diagnostic studies is not fully satisfactory, because sensitive searches have low precision. The objective of this study was to construct and validate better search strategies to identify diagnostic articles recorded on MEDLINE with special emphasis on precision. DESIGN: A comparative, retrospective analysis was conducted. Four medical journals were hand-searched for diagnostic studies published in 1989 and 1994. Four other journals were hand-searched for 1999. The three sets of studies identified were used as gold standards. A new search strategy was constructed and tested using the 1989-subset of studies and validated in both the 1994 and 1999 subsets. We identified candidate text words for search strategies using a word frequency analysis of the abstracts. According to the frequency of identified terms, searches were run for each term independently. The sensitivity, precision, and number needed to read (1/precision) of every candidate term were calculated. Terms with the highest sensitivity x precision product were used as free text terms in combination with the MeSH term "SENSITIVITY AND SPECIFICITY" using the Boolean operator OR. In the 1994 and 1999 subsets, we performed head-to-head comparisons of the currently available PubMed filter with the one we developed. MEASUREMENTS: The sensitivity, precision and the number needed to read (1/precision) were measured for different search filters. RESULTS: The most frequently occurring three truncated terms (diagnos*; predict* and accura*) in combination with the MeSH term "SENSITIVITY AND SPECIFICITY" produced a sensitivity of 98.1 percent (95% confidence interval: 89.9-99.9%) and a number needed to read of 8.3 (95% confidence interval: 6.7-11.3%). In direct comparisons of the new filter with the currently available one in PubMed using the 1994 and 1999 subsets, the new filter achieved better precision (12.0% versus 8.2% in 1994 and 5.0% versus 4.3% in 1999. The 95% confidence intervals for the differences range from 0.05% to 7.5% (p = 0.041) and -1.0% to 2.3% (p = 0.45), respectively). The new filter achieved slightly better sensitivities than the currently available one in both subsets, namely 98.1 and 96.1% (p = 0.32) versus 95.1 and 88.8% (p = 0.125). CONCLUSIONS: The quoted performance of the currently available filter for diagnostic studies in PubMed may be overstated. It appears that even single external validation may lead to over optimistic views of a filter's performance. Precision appears to be more unstable than sensitivity. In terms of sensitivity, our filter for diagnostic studies performed slightly better than the currently available one and it performed better with regards to precision in the 1994 subset. Additional research is required to determine whether these improvements are beneficial to searches in practice. (+info)
Exploring the boundaries of plausibility: empirical study of a key problem in the design of computer-based clinical simulations.
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All clinical simulation designers face the problem of identifying the plausible diagnostic and management options to include in their simulation models. This study explores the number of plausible diagnoses that exist for a given case, and how many subjects must work up a case before all plausible diagnoses are identified. Data derive from 144 residents and faculty physicians from 3 medical centers, each of whom worked 9 diagnostically challenging cases selected from a set of 36. Each subject generated up to 6 diagnostic hypotheses for each case, and each hypothesis was rated for plausibility by a clinician panel. Of the 2091 diagnoses generated, 399 (19.1%), an average of 11 per case, were considered plausible by study criteria. The distribution of plausibility ratings was found to be statistically case dependent. Averaged across cases, the final plausible diagnosis was generated by the 28th clinician (sd = 8) who worked the case. The results illustrate the richness and diversity of human cognition and the challenges these pose for creation of realistic simulations in biomedical domains. (+info)
Validation of electronic student encounter logs in an emergency medicine clerkship.
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Handheld electronic patient encounter logs offer opportunities to understand and enhance medical students' clinical experiences. Before using the data, the reliability of log entries needs to be verified. We assessed the sensitivity and specificity of handheld patient encounter logs by comparing documented entries with reliable external data sources. During an Emergency Medicine clerkship, medical students voluntarily recorded their patients' diagnoses in an Electronic Student Encounter Log (E-SEL) on handheld computers. We used patient demographics to match anonymous log entries with medical charts. Most students recorded 60% or more of their patient encounters and on average 60% of their patients' medical problems in the log. The false positive rate was 26% for patient encounters and 19% for patient problems. In general, students recorded more diagnoses in more detail than was available in the patient's ED chart. Improvements in the log's interface and documentation incentives should enhance the log's accuracy and utility. (+info)
The role of strategy and redundancy in diagnostic reasoning.
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BACKGROUND: Diagnostic reasoning is a key competence of physicians. We explored the effects of knowledge, practice and additional clinical information on strategy, redundancy and accuracy of diagnosing a peripheral neurological defect in the hand based on sensory examination. METHOD: Using an interactive computer simulation that includes 21 unique cases with seven sensory loss patterns and either concordant, neutral or discordant textual information, 21 3rd year medical students, 21 6th year and 21 senior neurology residents each examined 15 cases over the course of one session. An additional 23 psychology students examined 24 cases over two sessions, 12 cases per session. Subjects also took a seven-item MCQ exam of seven classical patterns presented visually. RESULTS: Knowledge of sensory patterns and diagnostic accuracy are highly correlated within groups (R2 = 0.64). The total amount of information gathered for incorrect diagnoses is no lower than that for correct diagnoses. Residents require significantly fewer tests than either psychology or 6th year students, who in turn require fewer than the 3rd year students (p < 0.001). The diagnostic accuracy of subjects is affected both by level of training (p < 0.001) and concordance of clinical information (p < 0.001). For discordant cases, refutation testing occurs significantly in 6th year students (p < 0.001) and residents (p < 0.01), but not in psychology or 3rd year students. Conversely, there is a stable 55% excess of confirmatory testing, independent of training or concordance. CONCLUSIONS: Knowledge and practice are both important for diagnostic success. For complex diagnostic situations reasoning components employing redundancy seem more essential than those using strategy. (+info)
A framework for clinical general practice and for research and teaching in the discipline.
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This paper uses three typical case stories from general practice to demonstrate that a GP simultaneously considers four dimensions when making a diagnosis and planning subsequent treatment of a patient in the consultation: (i). a biomedical dimension; (ii). a culture and context dimension; (iii). a medico-psychological dimension; and (iv). a network and social dimension. By taking this diagnostic and therapeutic approach, the GP adds value to the total performance of the health care system. It is demonstrated that a GP needs theoretical, research-based knowledge and skills within all four dimensions, and that it is necessary for a GP to work together with both medical and non-medical disciplines when defining the research and teaching agenda. It is stressed that consultation and communication skills are important tools for any doctor, and the value of continuity of care is discussed. Finally, the implications of the diagnostic approach with respect to planning research and teaching programmes are discussed, and the need for a better balance is stressed. (+info)
Programmed investigation unit.
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The programmed investigation unit (PIU) is a inpatient unit where a full range of investigational medicine can be organised. It provides the basic minimum nursing care and is suitable for ambulant patients who can care for themselves. Requests for admission to the PIU at the Royal Victoria Infirmary, Newcastle upon Tyne, come directly from clinical units, and the staff of these units perform some of the tests and remain responsible for the patient while she is in the unit. At present the unit caters only for female medical patients. The average waiting time for admission is three weeks, and because the unit now deals with most investigations the waiting time for admission to the female general medical wards has fallen considerably. The staff of the unit have gained expertise in diagnostic methods, while the nurses of general medical wards have been free to concentrate on nursing those patients who need it. Separating patients who need investigations from those on general medical wards seems a logical way of using resources and staff to best effect. (+info)
Recognizing childhood illnesses and their traditional explanations: exploring options for care-seeking interventions in the context of the IMCI strategy in rural Ghana.
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OBJECTIVES: Interventions that promote appropriate care-seeking for severely ill children have the potential to substantially reduce child mortality in developing countries, but little is known about the best approach to address the issue. This paper explores the relative importance of illness recognition as a barrier to care-seeking and the feasibility and potential impact of improving recognition. METHODS: The study combined qualitative and quantitative methods including in-depth interviews exploring the local illness classification system, a Rapid Anthropological Assessment (RAA) recording narratives of recent episodes of child illness and a survey designed to test the hypotheses that emerged from the RAA. RESULTS: Several danger symptoms were not recognized by caregivers. There were recognition problems which may not be feasibly addressed in an intervention. Other significant care-seeking barriers included classifying certain illnesses as 'not-for-hospital' and untreatable by modern medicine; problems of access; and frequent use of traditional medicines. CONCLUSION: The recognition component of any care-seeking intervention should identify the type of recognition problem present in the community. Many of the care-seeking barriers identified in the study revolved around the local illness classification system, which should be explored and built on as part of any care-seeking intervention. (+info)
Identifying diagnostic accuracy studies in EMBASE.
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OBJECTIVE: The objective was to develop and test search strategies to identify diagnostic articles recorded on EMBASE. METHODS: Four general medical journals were hand searched for diagnostic accuracy studies published in 1999. Identified studies served as a gold standard. Candidate terms for search strategies were identified using a word-frequency analysis of their abstracts. According to the frequency of identified terms, searches were run for each term independently. Sensitivity, precision, and number needed to read (NNR) (1/precision) of every candidate term were calculated. Terms with the highest "sensitivity*precision" product were used as free-text terms and combined into a final strategy using the Boolean operator "OR." RESULTS: The most frequently occurring eight terms (sensitiv* or detect* or accura* or specific* or reliab* or positive or negative or diagnos*) produced a sensitivity of 100% (95% confidence interval [CI] 94.1 to 100%) and an NNR of 27 (95% CI 21.0 to 34.8). The combination of the two truncated terms sensitiv* or detect* gave a sensitivity of 73.8% (95% CI 60.9 to 84.2%) and an NNR of 5.7 (95% CI 4.4 to 7.6). CONCLUSIONS: The identified search terms offer the choice of either reasonably sensitive or precise search strategies for the detection of diagnostic accuracy studies in EMBASE. The terms are useful both for busy health care professionals who value precision and for reviewers who value sensitivity. (+info)