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Percutaneous vertebroplasty (PVP) is considered an effective treatment for the back pain caused by osteoporotic vertebral compression fracture. The accuracy of PVP mainly depends on the surgeons' experience and multiple fluoroscopes during a traditional procedure. Puncture related complications were reported all over the world. To make the surgical procedure more precise and decrease the rate of puncture-related complications, our team applied a three-dimensional printing guide template to PVP to modify the traditional procedure. This protocol introduces how to model target vertebrae DICOM imaging data into three-dimensions in the software, how to simulate operation in this 3-D model, and how to use all of the surgical data to reconstruct a patient specific template for application. Using this template, surgeons can identify suitable puncture points accurately to improve the accuracy of the operation. The whole protocol includes: 1) diagnosis of the osteoporotic vertebral compression fracture; 2) acquisition of CT imaging of the target vertebra; 3) simulation of the operation in the software; 4) design and fabrication of the 3-D printing guide template; and 5) application of the template into an operation procedure.

Objective . In this randomized, nonblinded, controlled study, the feasibility and precision of "targeted percutaneous vertebroplasty" ("targeted PVP") for osteoporotic vertebral compression fracture (OVCF) was evaluated. Methods. A total of 42 patients, aged 50 to 87 years, with OVCF were randomly divided into 2 groups: A and B. Group A underwent "targeted PVP," and group B underwent traditional PVP with the guidance of C-arm fluoroscopy. Fluoroscopy times for skin puncture points (FTSPP), total radiation doses (TRD), total fluoroscopy times (TFT), and operation time were set as the main evaluation indicators. Results . FTSPP (1.52 ± 0.51 in group A vs 6.62 ± 2.58 in group B, U < .001), TRD (6.26 ± 1.51 in group A vs 11.32 ± 4.21 in group B, P < .001), TFT (16.57 ± 2.79 in group A vs 26.05 ± 6.18 in group B, P < .001), and operation time (20.05 ± 3.38 in group A vs 25.43 ±5.11 in group B, U < .001) were statistically different in the 2 groups. The incidence of cement leakage that occurred in group A (1/21, 4.76%) was significantly less than that in group B (9/21, 42.9%, P < 0.05). Conclusions . "Targeted PVP" may achieve (1) less skin positioning fluoroscopy times, less total fluoroscopy times and dose, shorter operation time, which is more precise than traditional PVP; (2) less incidence of cement leakage; and (3) visualization of the fractured vertebra, which is probably more valuable for the treatment of complicated OVCF patients.

Percutaneous vertebroplasty (PVP) is currently considered as an effective treatment for pain caused by acute osteoporotic vertebral compression fracture. Recently, puncture-related complications are increasingly reported. It's important to find a precise technique to reduce the puncture-related complications. We report a case and discussed the novel surgical technique with step-by-step operating procedures, to introduce the precise PVP assisted by a 3-dimensional printing guide template. Based on the preoperative CT scan and infrared scan data, a well-designed individual guide template could be established in a 3-dimensional reconstruction software and printed out by a 3-dimensional printer. In real operation, by matching the guide template to patient's back skin, cement needles' insertion orientation and depth were easily established. Only 14 times C-arm fluoroscopy with HDF mode (total exposure dose was 4.5 mSv) were required during the procedure. The operation took only 17 min. Cement distribution in the vertebral body was very good without any puncture-related complications. Pain was significantly relieved after surgery. In conclusion, the novel precise 3-dimensional printing guide template system may allow (1) comprehensive visualization of the fractured vertebral body and the individual surgical planning, (2) the perfect fitting between skin and guide template to ensure the puncture stability and accuracy, and (3) increased puncture precision and decreased puncture-related complications, surgical time and radiation exposure., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Objective: To describe a new technique for the efficient use of preoperative planning based on preoperative computed tomography-based three-dimensional (3D) model design for percutaneous vertebroplasty (PVP) in a patient with osteoporotic vertebral compression fracture., Methods: A 76-year-old woman with acute osteoporotic vertebral compression fracture (L1 level) accepted a novel precise PVP. A 3D model of thoracolumbar vertebrae (T12-L2) based on preoperative computed tomography scanning data and a simulative PVP (via a bilateral transpedicular approach) were built in MIMICS (Materialise Interactive Medical Image Control System) software. With the help of 3 radiopaque markers located at the skin of the back and preoperative digital design by MIMICS, bilateral skin entry points, needles direction including abduction angle and head inclination angle, and needle insertion depth were established., Results: During surgery, only 1 shot of fluoroscopy was required to confirm the skin entry points. The operation took only about 23 minutes and total patient exposure dose was 4.5 mSv. The intraoperative radiologic results showed that the cement distribution in the L1 vertebra was good without any puncture-related complications. The patient's visual analog scale score improved from 9 points preoperatively to 2 points postoperatively. The patient's preoperative Oswestry Disability Index score was 80 points, which improved to 57.8 points postoperatively., Conclusions: The novel precise PVP based on preoperative 3D model design allows 1) visualization of the morphology of the fractured vertebral body, 2) increased precision of puncture with decreasing incidence of puncture-related complications and reduced radiation exposure, and 3) less operation time, decreasing the learning curve of beginners with limited experience., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Problem: Efforts to evaluate and optimize the effectiveness of medical education have been limited by the difficulty of designing medical education research. Longitudinal, epidemiological views of educational outcomes can help overcome limitations, but these approaches require "bigger data"-more learners, sources, and time points. The rich data institutions collect on students and residents can be mined, however, ethical and practical barriers to using these data must first be overcome., Approach: In 2008, the authors established the Research on Medical Education Outcomes (ROMEO) Registry, an educational data registry modeled after patient registries. New York University School of Medicine students, residents, and fellows provide consent for routinely collected educational, performance, quality improvement, and clinical practice data to be compiled into a deidentified, longitudinal database. As of January 2015, this registry included 1,225 residents and fellows across 12 programs (71% consent rate) and 841 medical students (86% consent rate). Procedures ensuring voluntary informed consent are essential to ethical enrollment and data use. Substantial resources are required to provide access to and manage the data., Outcomes: The registry supports educational scholarship. Seventy-two studies using registry data have been presented or published. These focus on evaluating the curriculum, quality of care, and measurement quality and on assessing needs, competencies, skills development, transfer of skills to practice, remediation patterns, and links between education and patient outcomes., Next Steps: The authors are working to integrate assessment of relevant outcomes into the curriculum, maximize both the quantity and quality of the data, and expand the registry across institutions.

Objective: Standards terminologies may be large and complex, making their quality assurance challenging. Some terminology quality assurance (TQA) methodologies are based on abstraction networks (AbNs), compact terminology summaries. We have tested AbNs and the performance of related TQA methodologies on small terminology hierarchies. However, some standards terminologies, for example, SNOMED, are composed of very large hierarchies. Scaling AbN TQA techniques to such hierarchies poses a significant challenge. We present a scalable subject-based approach for AbN TQA., Methods: An innovative technique is presented for scaling TQA by creating a new kind of subject-based AbN called a subtaxonomy for large hierarchies. New hypotheses about concentrations of erroneous concepts within the AbN are introduced to guide scalable TQA., Results: We test the TQA methodology for a subject-based subtaxonomy for the Bleeding subhierarchy in SNOMED's large Clinical finding hierarchy. To test the error concentration hypotheses, three domain experts reviewed a sample of 300 concepts. A consensus-based evaluation identified 87 erroneous concepts. The subtaxonomy-based TQA methodology was shown to uncover statistically significantly more erroneous concepts when compared to a control sample., Discussion: The scalability of TQA methodologies is a challenge for large standards systems like SNOMED. We demonstrated innovative subject-based TQA techniques by identifying groups of concepts with a higher likelihood of having errors within the subtaxonomy. Scalability is achieved by reviewing a large hierarchy by subject., Conclusions: An innovative methodology for scaling the derivation of AbNs and a TQA methodology was shown to perform successfully for the largest hierarchy of SNOMED., (© The Author 2014. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Auditors of a large terminology, such as SNOMED CT, face a daunting challenge. To aid them in their efforts, it is essential to devise techniques that can automatically identify concepts warranting special attention. "Complex" concepts, which by their very nature are more difficult to model, fall neatly into this category. A special kind of grouping, called a partial-area, is utilized in the characterization of complex concepts. In particular, the complex concepts that are the focus of this work are those appearing in intersections of multiple partial-areas and are thus referred to as overlapping concepts. In a companion paper, an automatic methodology for identifying and partitioning the entire collection of overlapping concepts into disjoint, singly-rooted groups, that are more manageable to work with and comprehend, has been presented. The partitioning methodology formed the foundation for the development of an abstraction network for the overlapping concepts called a disjoint partial-area taxonomy. This new disjoint partial-area taxonomy offers a collection of semantically uniform partial-areas and is exploited herein as the basis for a novel auditing methodology. The review of the overlapping concepts is done in a top-down order within semantically uniform groups. These groups are themselves reviewed in a top-down order, which proceeds from the less complex to the more complex overlapping concepts. The results of applying the methodology to SNOMED's Specimen hierarchy are presented. Hypotheses regarding error ratios for overlapping concepts and between different kinds of overlapping concepts are formulated. Two phases of auditing the Specimen hierarchy for two releases of SNOMED are reported on. With the use of the double bootstrap and Fisher's exact test (two-tailed), the auditing of concepts and especially roots of overlapping partial-areas is shown to yield a statistically significant higher proportion of errors., (Copyright © 2011 Elsevier Inc. All rights reserved.)

A SNOMED CT-encoded problem list will be required to satisfy the Certification Criteria for Stage 2 "Meaningful Use" of the EHR incentive program. ICD-10-CM will be replacing ICD-9-CM as the reimbursement code set in the near future. Having a cross-map from SNOMED CT to ICD-10-CM will promote the use of SNOMED CT as the primary problem list terminology, while easing the transition to ICD-10-CM. This rule-based map will support semi-automatic generation of ICD-10-CM codes from SNOMED CT-encoded data. Among the different types of rules, the age rule is used to handle age-specific code assignment in ICD-10-CM. To supplement the manual process of creation of age rules, a special QA process was implemented to flag maps that were potentially missing age rules. The QA flagged 342 concepts for review (out of 7,277), of which 172 concepts (50.3%) were true positives. Without the special QA, many of the age rules would have been missed.

Medical terminologies are large and complex. Frequently, errors are hidden in this complexity. Our objective is to find such errors, which can be aided by deriving abstraction networks from a large terminology. Abstraction networks preserve important features but eliminate many minor details, which are often not useful for identifying errors. Providing visualizations for such abstraction networks aids auditors by allowing them to quickly focus on elements of interest within a terminology. Previously we introduced area taxonomies and partial area taxonomies for SNOMED CT. In this paper, two advanced, novel kinds of abstraction networks, the relationship-constrained partial area subtaxonomy and the root-constrained partial area subtaxonomy are defined and their benefits are demonstrated. We also describe BLUSNO, an innovative software tool for quickly generating and visualizing these SNOMED CT abstraction networks. BLUSNO is a dynamic, interactive system that provides quick access to well organized information about SNOMED CT.

Two mapping projects are currently underway, creating maps from SNOMED CT to ICD-10 and ICD-10-CM respectively. Even though the two projects belong to different organizations, there has been a lot of synergism between them. The ICD-10-CM map project heavily re-used the mapping methodology, tools and map data developed in the ICD-10 map project. An algorithm was derived to generate candidate ICD-10-CM map records from the ICD-10 map. We evaluated the algorithm in 5,264 SNOMED CT concepts common to both maps. 4,317 ICD-10-CM candidate maps could be generated from the ICD-10 map and 3,341 (77%) of the generated maps agreed with the published map. By priming the mapping process with candidate maps generated from the other map project, significant saving in time and effort in future phases of the two projects can be anticipated. The reasons for the discordance between the generated map and published map were also analyzed.

We analyzed 598 of 63,952 terms employed in problem list entries from seven major healthcare institutions that were not mapped with UMLS to SNOMED CT when preparing the NLM UMLS-CORE problem list subset. We intended to determine whether published or post-coordinated SNOMED concepts could accurately capture the problems as stated by the clinician and to characterize the workload for the local terminology manager. From the terms we analyzed, we estimate that 7.5% of the total terms represent ambiguous statements that require clarification. Of those terms which were unambiguous, we estimate that 38.1% could be encoded using the SNOMED CT January 2011 pre-coordinated (published core) content. 60.4% of unambiguous terms required post-coordination to capture the term meaning within the SNOMED model. Approximately 28.5% of post-coordinated content could not be fully defined and required primitive forms. This left 1.5% of unambiguous terms which were expressed with meaning which could not be represented in SNOMED CT. We estimate from our study that 98.5% of clinical terms unambiguously suggested for the problem list can be equated to published concepts or can be modeled with SNOMED CT but that roughly one in four SNOMED modeled expressions fail to represent the full meaning of the term. Implications for the business model of the local terminology manager and the development of SNOMED CT are discussed.

Three Problem List Terminologies (PLT) were tested using a web-based application simulating a clinical data entry environment to evaluate coverage and coding efficiency. The three PLTs were: the CORE Problem List Subset of SNOMED CT, a clinical subset extracted from the full SNOMED CT and the PLT currently used at the Mayo Clinic. Candidate problem statements were randomly extracted from free text problem list entries contained in two electronic medical record systems. Physician reviewers searched for concepts in one of the three PLTs that most closely matched a problem statement. Altogether 45 reviewers reviewed 15 problems each. The coverage of the much smaller CORE Subset was comparable to Clinical SNOMED for combined exact or partial matches. The CORE Subset required the shortest time to find a concept. This may be related to the smaller size of the pick lists for the CORE Subset.

The goal of this paper is to audit null-annotated parent-child pairs in the UMLS Metathesaurus. We have developed techniques for identifying suspicious pairs with high likelihood of errors by using inconsistencies between the hierarchical relationships of the Metathesaurus and the Semantic Network. Two formal conditions, called semantic inversion and lack of ancestry are investigated. Analyzing two corresponding samples shows that semantic inversion is significantly more likely to indicate an error than lack of ancestry, which in turn is more likely to indicate errors than a consistent configuration. We also discuss cases of parent-child pairs with semantic inversion that may be corrected by disambiguating the child.

Objective: Each Unified Medical Language System (UMLS) concept is assigned one or more semantic types (ST). A dynamic methodology for aiding an auditor in finding concepts that are missing the assignment of a given ST, S is presented., Design: The first part of the methodology exploits the previously introduced Refined Semantic Network and accompanying refined semantic types (RST) to help narrow the search space for offending concepts. The auditing is focused in a neighborhood surrounding the extent of an RST, T (of S) called an envelope, consisting of parents and children of concepts in the extent. The audit moves outward as long as missing assignments are discovered. In the second part, concepts not reached previously are processed and reassigned T as needed during the processing of S's other RSTs. The set of such concepts is expanded in a similar way to that in the first part., Measurements: The number of errors discovered is reported. To measure the methodology's efficiency, "error hit rates" (i.e., errors found in concepts examined) are computed., Results: The methodology was applied to three STs: Experimental Model of Disease (EMD), Environmental Effect of Humans, and Governmental or Regulatory Activity. The EMD experienced the most drastic change. For its RST "EMD intersection Neoplastic Process" (RST "EMD") with only 33 (31) original concepts, 915 (134) concepts were found by the first (second) part to be missing the EMD assignment. Changes to the other two STs were smaller., Conclusion: The results show that the proposed auditing methodology can help to effectively and efficiently identify concepts lacking the assignment of a particular semantic type.

Objective: Synonym-substitution algorithms have been developed for the purpose of matching source vocabulary terms with existing Unified Medical Language System (UMLS) terms during the integration process. A drawback is the possible explosion in the number of newly generated (potential) synonyms, which can tax computational and expert review resources. Experiments are run using a synonym-substitution approach based on WordNet to see how constraining two methodological parameters, namely, "maximum number of substitutions per term" and "maximum term length," affects performance. Our hypothesis is that these values can be constrained rather tightly--thus greatly speeding up the methodology--without a marked decline in the additional matches produced. Furthermore, we investigate whether a limitation on only the first of the two parameters is sufficient to achieve the same results., Methods: A four-stage synonym-substitution methodology using WordNet is presented. A group of experiments is carried out in which the two methodological parameters "maximum number of substitutions per term" and "maximum term length" are varied. The purpose is to examine their effect on the growth in the number of potential synonyms generated and the associated loss of results. The experiments are based on the re-integration of the "Minimal Standard Terminology" (MST) into the UMLS. Synonym-substitution matches found to be inconsistent with the current content of the UMLS and thus deemed to be incorrect are further manually scrutinized as an audit of the original integration of the MST., Results: An increase of 11% in the number of "MST term/UMLS term" matches was achieved using the synonym-substitution methodology. Importantly, this result prevailed when tight threshold values (such as a maximum of two synonym substitutions per term) were imposed on the parameters. Furthermore, it was found that limiting only the "maximum number of substitutions per term" parameter was sufficient to obtain the performance enhancement. During the additional audit phase, a number of the reported mismatches were actually seen to be correct, representing an additional 10% increase in the number of matches obtained., Conclusion: A synonym-substitution methodology that utilizes WordNet is a useful automated aide in UMLS source integration. Experiments showed that there was a significant speed-up but no degradation in match results when the methodology's "maximum number of substitutions per term" parameter was relatively tightly constrained. The methodology also helped to discover errors in the MST's original integration, and improve the quality of the UMLS's conceptual content.

Limited resources and the sheer volume of concepts make auditing a large terminology, such as SNOMED CT, a daunting task. It is essential to devise techniques that can aid an auditor by automatically identifying concepts that deserve attention. A methodology for this purpose based on a previously introduced abstraction network (called the p-area taxonomy) for a SNOMED CT hierarchy is presented. The methodology algorithmically gathers concepts appearing in certain overlapping subsets, defined exclusively with respect to the p-area taxonomy, for review. The results of applying the methodology to SNOMED's Specimen hierarchy are presented. These results are compared against a control sample composed of concepts residing in subsets without the overlaps. With the use of the double bootstrap, the concept group produced by our methodology is shown to yield a statistically significant higher proportion of error discoveries.

SNOMED CT is an extensive terminology with an attendant amount of complexity. Two measures are proposed for quantifying that complexity. Both are based on abstraction networks, called the area taxonomy and the partial-area taxonomy, that provide, for example, distributions of the relationships within a SNOMED hierarchy. The complexity measures are employed specifically to track the complexity of versions of the Specimen hierarchy of SNOMED before and after it is put through an auditing process. The pre-audit and post-audit versions are compared. The results show that the auditing process indeed leads to a simplification of the terminology's structure.