Development of a Google-based search engine for data mining radiology reports

Searching Full-Text Anatomic Pathology Reports Using Business Intelligence Software

Although the laboratory information system has largely solved the problem of storing anatomic pathology reports and disseminating their contents across the healthcare system, the retrospective query of anatomic pathology reports remains an area for improvement across laboratory information system vendors. Our institution desired the ability to query our repository of anatomic pathology reports for clinical, operational, research, and educational purposes. To address this need, we developed a full-text anatomic pathology search tool using the business intelligence software, Tableau. Our search tool allows users to query the 333,685 anatomic pathology reports from our institutional clinical relational database using the business intelligence tool's built-in regular expression functionality. Users securely access the search tool using any web browser, thereby avoiding the cost of installing or maintaining software on users' computers. This tool is laboratory information system vendor agnostic and as many institutions already subscribe to business intelligence software, we believe this solution could be easily reproduced at other institutions and in other clinical departments.

Google Medical Update: Why Is the Search Engine Decreasing Visibility of Health and Medical Information Websites?

The Google search engine answers many health and medical information queries every day. People have become used to searching for this type of information. This paper presents a study which examined the visibility of health and medical information websites. The purpose of this study was to find out why Google is decreasing the visibility of such websites and how to measure this decrease. Since August 2018, Google has been more rigorously rating these websites, since they can potentially impact people’s health. The method of the study was to collect data about the visibility of health and medical information websites in sequential time snapshots. Visibility consists of combined data of unique keywords, positions, and URL results. The sample under study was made up of 21 websites selected from 10 European countries. The findings reveal that in sequential time snapshots, search visibility decreased. The decrease was not dependent on the country or the language. The main reason why Google is decreasing the visibility of such websites is that they do not meet high ranking criteria.

Searching Data: A Review of Observational Data Retrieval Practices in Selected Disciplines

A cross‐disciplinary examination of the user behaviors involved in seeking and evaluating data is surprisingly absent from the research data discussion. This review explores the data retrieval literature to identify commonalities in how users search for and evaluate observational research data in selected disciplines. Two analytical frameworks, rooted in information retrieval and science and technology studies, are used to identify key similarities in practices as a first step toward developing a model describing data retrieval.

A Systematic Review on Healthcare Analytics: Application and Theoretical Perspective of Data Mining

The growing healthcare industry is generating a large volume of useful data on patient demographics, treatment plans, payment, and insurance coverage—attracting the attention of clinicians and scientists alike. In recent years, a number of peer-reviewed articles have addressed different dimensions of data mining application in healthcare. However, the lack of a comprehensive and systematic narrative motivated us to construct a literature review on this topic. In this paper, we present a review of the literature on healthcare analytics using data mining and big data. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we conducted a database search between 2005 and 2016. Critical elements of the selected studies—healthcare sub-areas, data mining techniques, types of analytics, data, and data sources—were extracted to provide a systematic view of development in this field and possible future directions. We found that the existing literature mostly examines analytics in clinical and administrative decision-making. Use of human-generated data is predominant considering the wide adoption of Electronic Medical Record in clinical care. However, analytics based on website and social media data has been increasing in recent years. Lack of prescriptive analytics in practice and integration of domain expert knowledge in the decision-making process emphasizes the necessity of future research.

Subradiographic Foot and Ankle Fractures and Bone Contusions Detected by MRI in Elite Ice Hockey Players

BACKGROUND

In ice hockey players, serious bone injuries in the foot and ankle, especially those attributed to impact from the moving puck, may be radiographically occult and underrecognized.

PURPOSE/HYPOTHESIS

The purpose of this research was to study foot and ankle bone injuries detected with magnetic resonance imaging (MRI) that occurred in elite hockey players. The hypothesis was that these injuries predominate medially, especially when caused by the impact from the puck, and are associated with prolonged lost playing time.

STUDY DESIGN

Case series; Level of evidence, 4.

METHODS

Three independent observers, blinded to the mechanism of injury, retrospectively reviewed foot and ankle MRI examinations acquired after 31 acute injuries that occurred in 27 elite ice hockey players who had no radiographically visible fractures. Bone abnormalities were classified as fractures or varying degrees of contusion based on predetermined definitions. Interobserver agreement was analyzed with kappa statistics. The association between the injury mechanism and the bones involved was examined with the Fisher exact test. A t test was applied to determine if MRI evidence of a severe bone injury (defined as either a fracture or a high-grade bone contusion) was associated with longer recovery times, when return-to-play information was available.

RESULTS

The observers identified at least 1 bone injury in 27 of the 31 MRI examinations, including 10 with radiographically occult fractures. Agreement among the 3 observers for injury categorization was substantial (κ = 0.76). Seventeen injuries were caused by a direct blow (15 from a moving puck, 2 from an uncertain source), resulting in 6 fractures and 6 high-grade bone contusions, with 14 of the 17 involving a medial bone (medial malleolus, navicular, or first metatarsal base). Compared with other mechanisms, direct impaction was statistically more likely to result in a severe bone injury and to involve the medial foot and ankle. In 20 injuries where return-to-play information was available, players with severe bone injuries missed a mean of 10.6 games compared with 2.4 games for other players (P = .05).

CONCLUSION

MRI can show severe bone injuries that are not visible radiographically in ice hockey players. Most fractures and high-grade contusions involve the medial ankle and midfoot bones, can be caused by direct blows from the puck, and are associated with prolonged recovery times.

An information retrieval system for computerized patient records in the context of a daily hospital practice: the example of the Léon Bérard Cancer Center (France)

BACKGROUND

A full-text search tool was introduced into the daily practice of Léon Bérard Center (France), a health care facility devoted to treatment of cancer. This tool was integrated into the hospital information system by the IT department having been granted full autonomy to improve the system.

OBJECTIVES

To describe the development and various uses of a tool for full-text search of computerized patient records.

METHODS

The technology is based on Solr, an open-source search engine. It is a web-based application that processes HTTP requests and returns HTTP responses. A data processing pipeline that retrieves data from different repositories, normalizes, cleans and publishes it to Solr, was integrated in the information system of the Leon Bérard center. The IT department developed also user interfaces to allow users to access the search engine within the computerized medical record of the patient.

RESULTS

From January to May 2013, 500 queries were launched per month by an average of 140 different users. Several usages of the tool were described, as follows: medical management of patients, medical research, and improving the traceability of medical care in medical records. The sensitivity of the tool for detecting the medical records of patients diagnosed with both breast cancer and diabetes was 83.0%, and its positive predictive value was 48.7% (gold standard: manual screening by a clinical research assistant).

CONCLUSION

The project demonstrates that the introduction of full-text-search tools allowed practitioners to use unstructured medical information for various purposes.

The accuracy of Internet search engines to predict diagnoses from symptoms can be assessed with a validated scoring system

PURPOSE

To validate a scoring system that evaluates the ability of Internet search engines to correctly predict diagnoses when symptoms are used as search terms.

METHODS

We developed a five point scoring system to evaluate the diagnostic accuracy of Internet search engines. We identified twenty diagnoses common to a primary care setting to validate the scoring system. One investigator entered the symptoms for each diagnosis into three Internet search engines (Google, Bing, and Ask) and saved the first five webpages from each search. Other investigators reviewed the webpages and assigned a diagnostic accuracy score. They rescored a random sample of webpages two weeks later. To validate the five point scoring system, we calculated convergent validity and test-retest reliability using Kendall's W and Spearman's rho, respectively. We used the Kruskal-Wallis test to look for differences in accuracy scores for the three Internet search engines.

RESULTS

A total of 600 webpages were reviewed. Kendall's W for the raters was 0.71 (p<0.0001). Spearman's rho for test-retest reliability was 0.72 (p<0.0001). There was no difference in scores based on Internet search engine. We found a significant difference in scores based on the webpage's order on the Internet search engine webpage (p=0.007). Pairwise comparisons revealed higher scores in the first webpages vs. the fourth (corr p=0.009) and fifth (corr p=0.017). However, this significance was lost when creating composite scores.

CONCLUSIONS

The five point scoring system to assess diagnostic accuracy of Internet search engines is a valid and reliable instrument. The scoring system may be used in future Internet research.

Automated measurement of pediatric cranial bone thickness and density from clinical computed tomography

Skull thickness and density measures of normal pediatric crania would inform multiple disciplines including neurosurgery, optical and magnetoelectrophysiological imaging, and biomechanical modeling of head trauma. We report on a new method for automated extraction of in vivo skull thickness and density measures of pediatric crania based on x-ray computed tomography scans (CT). Data were obtained from a clinical image repository for pediatric populations in whom no pathology was noted. Skull thickness and density measures were systematically obtained across the calvarium. We find a set of measures that correlated with physiological age that are likely to prove useful in multiple disciplines.

The future of the radiology information system

OBJECTIVE

Today in the hospital setting, several functions of the radiology information system (RIS), including order entry, patient registration, report repository, and the physician directory, have moved to enterprise electronic medical records. Some observers might conclude that the RIS is going away. In this article, we contend that because of the maturity of the RIS market compared with other areas of the health care enterprise, radiology has a unique opportunity to innovate.

CONCLUSION

While most of the hospital enterprise spends the next several years going through the digital transformation converting from paper to a digital format, radiology can leap ahead in its use of analytics and information technology. This article presents a summary of new RIS functions still maturing and open to innovation in the RIS market.

Bridging the text-image gap: a decision support tool for real-time PACS browsing

In this paper, we introduce an ontology-based technology that bridges the gap between MR images on the one hand and knowledge sources on the other hand. The proposed technology allows the user to express interest in a body region by selecting this region on the MR image he or she is viewing with a mouse device. The proposed technology infers the intended body structure from the manual selection and searches the external knowledge source for pertinent information. This technology can be used to bridge the gap between image data in the clinical workflow and (external) knowledge sources that help to assess the case with increased certainty, accuracy, and efficiency. We evaluate an instance of the proposed technology in the neurodomain by means of a user study in which three neuroradiologists participated. The user study shows that the technology has high recall (>95%) when it comes to inferring the intended brain region from the participant's manual selection. We are confident that this helps to increase the experience of browsing external knowledge sources.

Evaluation of negation and uncertainty detection and its impact on precision and recall in search

Radiology reports contain information that can be mined using a search engine for teaching, research, and quality assurance purposes. Current search engines look for exact matches to the search term, but they do not differentiate between reports in which the search term appears in a positive context (i.e., being present) from those in which the search term appears in the context of negation and uncertainty. We describe RadReportMiner, a context-aware search engine, and compare its retrieval performance with a generic search engine, Google Desktop. We created a corpus of 464 radiology reports which described at least one of five findings (appendicitis, hydronephrosis, fracture, optic neuritis, and pneumonia). Each report was classified by a radiologist as positive (finding described to be present) or negative (finding described to be absent or uncertain). The same reports were then classified by RadReportMiner and Google Desktop. RadReportMiner achieved a higher precision (81%), compared with Google Desktop (27%; p < 0.0001). RadReportMiner had a lower recall (72%) compared with Google Desktop (87%; p = 0.006). We conclude that adding negation and uncertainty identification to a word-based radiology report search engine improves the precision of search results over a search engine that does not take this information into account. Our approach may be useful to adopt into current report retrieval systems to help radiologists to more accurately search for radiology reports.