Dataset Information

Structured reporting of x-rays for atraumatic shoulder pain: advantages over free text?

ABSTRACT: BACKGROUND:To analyse structured and free text reports of shoulder X-ray examinations evaluating the quality of reports and potential contributions to clinical decision-making. METHODS:We acquired both standard free text and structured reports of 31 patients with a painful shoulder without history of previous trauma who received X-ray exams. A template was created for the structured report based on the template ID 0000154 (Shoulder X-ray) from radreport.org using online software with clickable decision trees with concomitant generation of structured semantic reports. All reports were evaluated regarding overall quality and key features: content, information extraction and clinical relevance. RESULTS:Two experienced orthopaedic surgeons reviewed and rated structured and free text reports of 31 patients independently. The structured reports achieved significantly higher median ratings in all key features evaluated (P?

SUBMITTER: Schoppe F

PROVIDER: S-EPMC6029150 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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Structured reporting of x-rays for atraumatic shoulder pain: advantages over free text?

Schöppe Franziska F Sommer Wieland H WH Schmidutz Florian F Pförringer Dominik D Armbruster Marco M Paprottka Karolin J KJ Plum Jessica L V JLV Sabel Bastian O BO Meinel Felix G FG Sommer Nora N NN

BMC medical imaging 20180703 1

<h4>Background</h4>To analyse structured and free text reports of shoulder X-ray examinations evaluating the quality of reports and potential contributions to clinical decision-making.<h4>Methods</h4>We acquired both standard free text and structured reports of 31 patients with a painful shoulder without history of previous trauma who received X-ray exams. A template was created for the structured report based on the template ID 0000154 (Shoulder X-ray) from radreport.org using online software w ...[more]

PMID: 29970014

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Project description:BackgroundSocial and behavioral determinants of health (SBDH) are environmental and behavioral factors that often impede disease management and result in sexually transmitted infections. Despite their importance, SBDH are inconsistently documented in electronic health records (EHRs) and typically collected only in an unstructured format. Evidence suggests that structured data elements present in EHRs can contribute further to identify SBDH in the patient record.ObjectiveExplore the automated inference of both the presence of SBDH documentation and individual SBDH risk factors in patient records. Compare the relative ability of clinical notes and structured EHR data, such as laboratory measurements and diagnoses, to support inference.MethodsWe attempt to infer the presence of SBDH documentation in patient records, as well as patient status of 11 SBDH, including alcohol abuse, homelessness, and sexual orientation. We compare classification performance when considering clinical notes only, structured data only, and notes and structured data together. We perform an error analysis across several SBDH risk factors.ResultsClassification models inferring the presence of SBDH documentation achieved good performance (F1 score: 92.7-78.7; F1 considered as the primary evaluation metric). Performance was variable for models inferring patient SBDH risk status; results ranged from F1?=?82.7 for LGBT (lesbian, gay, bisexual, and transgender) status to F1?=?28.5 for intravenous drug use. Error analysis demonstrated that lexical diversity and documentation of historical SBDH status challenge inference of patient SBDH status. Three of five classifiers inferring topic-specific SBDH documentation and 10 of 11 patient SBDH status classifiers achieved highest performance when trained using both clinical notes and structured data.ConclusionOur findings suggest that combining clinical free-text notes and structured data provide the best approach in classifying patient SBDH status. Inferring patient SBDH status is most challenging among SBDH with low prevalence and high lexical diversity.

Project description:BackgroundThe electronic medical record (EMR) contains a rich source of information that could be harnessed for epidemic surveillance. We asked if structured EMR data could be coupled with computerized processing of free-text clinical entries to enhance detection of acute respiratory infections (ARI).MethodologyA manual review of EMR records related to 15,377 outpatient visits uncovered 280 reference cases of ARI. We used logistic regression with backward elimination to determine which among candidate structured EMR parameters (diagnostic codes, vital signs and orders for tests, imaging and medications) contributed to the detection of those reference cases. We also developed a computerized free-text search to identify clinical notes documenting at least two non-negated ARI symptoms. We then used heuristics to build case-detection algorithms that best combined the retained structured EMR parameters with the results of the text analysis.Principal findingsAn adjusted grouping of diagnostic codes identified reference ARI patients with a sensitivity of 79%, a specificity of 96% and a positive predictive value (PPV) of 32%. Of the 21 additional structured clinical parameters considered, two contributed significantly to ARI detection: new prescriptions for cough remedies and elevations in body temperature to at least 38°C. Together with the diagnostic codes, these parameters increased detection sensitivity to 87%, but specificity and PPV declined to 95% and 25%, respectively. Adding text analysis increased sensitivity to 99%, but PPV dropped further to 14%. Algorithms that required satisfying both a query of structured EMR parameters as well as text analysis disclosed PPVs of 52-68% and retained sensitivities of 69-73%.ConclusionStructured EMR parameters and free-text analyses can be combined into algorithms that can detect ARI cases with new levels of sensitivity or precision. These results highlight potential paths by which repurposed EMR information could facilitate the discovery of epidemics before they cause mass casualties.

Project description:BackgroundThe impact of atraumatic shoulder instability (ASI) on patients can be extensive, its management complex, with a biopsychosocial approach recommended. Currently how physiotherapists manage ASI is unknown or the extent to which current clinical practice aligns with existing evidence. At the time of this study no national guidelines or consensus to direct practice existed.MethodsA cross-sectional electronic survey was distributed between July-September 2018, targeting UK-based physiotherapists managing shoulder pathology. Respondents were invited to describe their management of ASI, and rate their awareness and utilisation of various treatment techniques on a Likert-scale; median and interquartile ranges were calculated. Free text survey items were analysed using quantitative content analysis (QCA) to identify codes and categories. Means and percentages were calculated to summarise QCA and descriptive data.ResultsValid survey responses were analysed (n = 135). Respondents had between 2 and 39 years of physiotherapy experience (mean = 13.9 years); the majority (71.1 %) reported that ASI made up < 10 % of their caseload. Only 22.9 % (n = 31/135) of respondents reported feeling 'very confident' in managing ASI; the majority feeling 'somewhat confident' (70.4 %, n = 95/135) or 'not confident' (6.7 %, n = 9/135). The majority of respondents (59.3 %) used an ASI classification system, > 90 % citing the Stanmore Classification. Physiotherapists adapted their management according to clinical presentation, responding to differing biopsychosocial needs of the patient scenario. Most respondents (> 80 %) did not use a protocol to guide their management. Exercise was the most utilised management approach for ASI, followed by education; novel treatment strategies, including cortical rehabilitation, were also reported.ConclusionFindings indicate physiotherapists utilise a wide range of treatment strategies and respond to biopsychosocial cues when managing patients with ASI. The majority reported not being very confident in managing this condition, however only a minority use rehabilitation protocols to support their management. Some interventions that respondents reported using lacked evidence to support their use in ASI management and further research regarding effectiveness is required. Guidelines have been published since this survey; the impact of these will need evaluating to determine their effectiveness in the future.

Project description:A previous study has suggested that it is uncommon for patients with chronic bothersome low back pain (LBP), who consult the secondary health care sector, to report at least four consecutive weeks without such bothersome pain in 1 year. It is not yet known, however, how many days of the week they experience pain throughout the year.The current study analyzed data collected in two randomized clinical studies conducted in 2007-9 on patients with back pain (Study 1 and 2). Study participants were patients with LBP for more than 2 months, one group with MRI-defined Modic changes (Study 1) and the other without any pathological explanation for the pain (Study 2). In both studies, participants were followed over 1 year with weekly automated text messages (SMS-Track). Each week they reported the number of days they had experienced bothersome LBP (0-7 days). The number of weeks with 7 days of bothersome LBP was calculated for both study groups. As baseline and outcome characteristics were similar between the intervention and control groups in each study, the data from treatment and control groups in each study were analyzed together, regardless of treatment allocation and the results compared between the two study samples.The proportion of patients reporting bothersome LBP all days of the week ranged from 0 to 100 %, with the findings arranged in a U-shaped curve. The pain frequency patterns were remarkably similar for the two study samples. At one extreme, 31 % of participants reported 0-10 % of weeks with daily LBP. At the other extreme, 25 % of participants reported 91-100 % of weeks with daily LBP. The distribution between these values was also very similar for the two groups.This study revealed there to be considerable variation in weekly persistence of symptoms during 1 year in patients from the secondary care sector with chronic LBP. The results range from bothersome pain each day of the week, every week of the year, to no weeks at all with 7 days of pain. Interestingly, this pattern is near-identical in the two study samples; those with non-specific LBP and those with LBP and Modic changes. This heterogeneic pain profile in patients with chronic LBP deserves to be further investigated.

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Structured reporting of x-rays for atraumatic shoulder pain: advantages over free text?

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Structured reporting of x-rays for atraumatic shoulder pain: advantages over free text?

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