Nomenclature Of Medicine-Clinical Terms Research Articles

Influenza and Respiratory Virus Surveillance, Vaccine Uptake, and Effectiveness at a Time of Cocirculating COVID-19: Protocol for the English Primary Care Sentinel System for 2020-2021.

BackgroundThe Oxford–Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) and Public Health England (PHE) are commencing their 54th season of collaboration at a time when SARS-CoV-2 infections are likely to be cocirculating with the usual winter infections.ObjectiveThe aim of this study is to conduct surveillance of influenza and other monitored respiratory conditions and to report on vaccine uptake and effectiveness using nationally representative surveillance data extracted from primary care computerized medical records systems. We also aim to have general practices collect virology and serology specimens and to participate in trials and other interventional research.MethodsThe RCGP RSC network comprises over 1700 general practices in England and Wales. We will extract pseudonymized data twice weekly and are migrating to a system of daily extracts. First, we will collect pseudonymized, routine, coded clinical data for the surveillance of monitored and unexpected conditions; data on vaccine exposure and adverse events of interest; and data on approved research study outcomes. Second, we will provide dashboards to give general practices feedback about levels of care and data quality, as compared to other network practices. We will focus on collecting data on influenza-like illness, upper and lower respiratory tract infections, and suspected COVID-19. Third, approximately 300 practices will participate in the 2020-2021 virology and serology surveillance; this will include responsive surveillance and long-term follow-up of previous SARS-CoV-2 infections. Fourth, member practices will be able to recruit volunteer patients to trials, including early interventions to improve COVID-19 outcomes and point-of-care testing. Lastly, the legal basis for our surveillance with PHE is Regulation 3 of the Health Service (Control of Patient Information) Regulations 2002; other studies require appropriate ethical approval.ResultsThe RCGP RSC network has tripled in size; there were previously 100 virology practices and 500 practices overall in the network and we now have 322 and 1724, respectively. The Oxford–RCGP Clinical Informatics Digital Hub (ORCHID) secure networks enable the daily analysis of the extended network; currently, 1076 practices are uploaded. We are implementing a central swab distribution system for patients self-swabbing at home in addition to in-practice sampling. We have converted all our primary care coding to Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) coding. Throughout spring and summer 2020, the network has continued to collect specimens in preparation for the winter or for any second wave of COVID-19 cases. We have collected 5404 swabs and detected 623 cases of COVID-19 through extended virological sampling, and 19,341 samples have been collected for serology. This shows our preparedness for the winter season.ConclusionsThe COVID-19 pandemic has been associated with a groundswell of general practices joining our network. It has also created a permissive environment in which we have developed the capacity and capability of the national primary care surveillance systems and our unique public health institute, the RCGP and University of Oxford collaboration.

Structured Data Capture for Oncology.

Lack of interoperability is one of the greatest challenges facing healthcare informatics. Recent interoperability efforts have focused primarily on data transmission and generally ignore data capture standardization. Structured Data Capture (SDC) is an open-source technical framework that enables the capture and exchange of standardized and structured data in interoperable data entry forms (DEFs) at the point of care. Some of SDC’s primary use cases concern complex oncology data such as anatomic pathology, biomarkers, and clinical oncology data collection and reporting. Its interoperability goals are the preservation of semantic, contextual, and structural integrity of the captured data throughout the data’s lifespan. SDC documents are written in eXtensible Markup Language (XML) and are therefore computer readable, yet technology agnostic—SDC can be implemented by any EHR vendor or registry. Any SDC-capable system can render an SDC XML file into a DEF, receive and parse an SDC transmission, and regenerate the original SDC form as a DEF or synoptic report with the response data intact. SDC is therefore able to facilitate interoperable data capture and exchange for patient care, clinical trials, cancer surveillance and public health needs, clinical research, and computable care guidelines. The usability of SDC-captured oncology data is enhanced when the SDC data elements are mapped to standard terminologies. For example, an SDC map to Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) enables aggregation of SDC data with other related data sets and permits advanced queries and groupings on the basis of SNOMED CT concept attributes and description logic. SDC supports terminology maps using separate map files or as terminology codes embedded in an SDC document.

Strategies for Adopting and Implementing SNOMED CT in Korea.

ObjectivesThe objective of this study was to introduce the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT), to describe use cases of SNOMED CT with the barriers and facilitators, and finally, to propose strategies for adopting and implementing SNOMED CT in Korea as a member of SNOMED International.MethodsWe reviewed a collection of SNOMED CT documents, such as introductory materials, practical guides, technical specifications, and reference materials provided by SNOMED International and the literature on SNOMED CT published by researchers to identify use cases of SNOMED CT with barriers and facilitators. We also surveyed the attendees of SNOMED CT education and training series offered by the Korea Human Resource Development Institute for Health and Welfare to identify perceived barriers to adopting SNOMED CT in Korea.ResultsWe identified the barriers and facilitators to adopt SNOMED CT experienced by international terminology experts and prospective Korean users. They were related to governance and infrastructure, support services for use, education and training programs, use cases, and vendor capability to implement SNOMED CT. Based on these findings, we identified strategies for adopting and implementing SNOMED CT in Korea. They included the establishment of SNOMED CT management infrastructure, the development of SNOMED CT education and training programs for various user groups, the provision of support services for SNOMED CT use, and the development of SNOMED CT use cases.ConclusionsThese strategies for the adoption and implementation of SNOMED CT need to be executed step by step.

Use of the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) for Processing Free Text in Health Care: Systematic Scoping Review.

BackgroundInteroperability and secondary use of data is a challenge in health care. Specifically, the reuse of clinical free text remains an unresolved problem. The Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) has become the universal language of health care and presents characteristics of a natural language. Its use to represent clinical free text could constitute a solution to improve interoperability.ObjectiveAlthough the use of SNOMED and SNOMED CT has already been reviewed, its specific use in processing and representing unstructured data such as clinical free text has not. This review aims to better understand SNOMED CT's use for representing free text in medicine.MethodsA scoping review was performed on the topic by searching MEDLINE, Embase, and Web of Science for publications featuring free-text processing and SNOMED CT. A recursive reference review was conducted to broaden the scope of research. The review covered the type of processed data, the targeted language, the goal of the terminology binding, the method used and, when appropriate, the specific software used.ResultsIn total, 76 publications were selected for an extensive study. The language targeted by publications was 91% (n=69) English. The most frequent types of documents for which the terminology was used are complementary exam reports (n=18, 24%) and narrative notes (n=16, 21%). Mapping to SNOMED CT was the final goal of the research in 21% (n=16) of publications and a part of the final goal in 33% (n=25). The main objectives of mapping are information extraction (n=44, 39%), feature in a classification task (n=26, 23%), and data normalization (n=23, 20%). The method used was rule-based in 70% (n=53) of publications, hybrid in 11% (n=8), and machine learning in 5% (n=4). In total, 12 different software packages were used to map text to SNOMED CT concepts, the most frequent being Medtex, Mayo Clinic Vocabulary Server, and Medical Text Extraction Reasoning and Mapping System. Full terminology was used in 64% (n=49) of publications, whereas only a subset was used in 30% (n=23) of publications. Postcoordination was proposed in 17% (n=13) of publications, and only 5% (n=4) of publications specifically mentioned the use of the compositional grammar.ConclusionsSNOMED CT has been largely used to represent free-text data, most frequently with rule-based approaches, in English. However, currently, there is no easy solution for mapping free text to this terminology and to perform automatic postcoordination. Most solutions conceive SNOMED CT as a simple terminology rather than as a compositional bag of ontologies. Since 2012, the number of publications on this subject per year has decreased. However, the need for formal semantic representation of free text in health care is high, and automatic encoding into a compositional ontology could be a solution.

Community-based pharmacy use of the Pharmacist eCare Plan: A retrospective review

BackgroundPharmacists in community-based settings document patient care using the Pharmacist eCare Plan (PeCP). ObjectiveTo conduct a pilot evaluation of the PeCP use and documentation of Systemized Nomenclature of Medicine Clinical Terms (SNOMED CT) codes within select community-based pharmacies. Practice descriptionMoose Pharmacy operates 7 locations in rural North Carolina that are part of the Community Pharmacy Enhanced Services Network (CPESN). The Moose Pharmacy Medication Adherence Program (MooseMAP) targets patients with a chronic condition who would benefit from medication synchronization, adherence packaging, and monthly calls. Practice innovationCPESN pharmacies use the PeCP to track a patient’s concerns, goals, interventions, and medication-related information. The PeCP standard requires pharmacies to detail a patient’s current medication regimen and health concerns as well as the pharmacy’s interventions and patient’s health over time.Evaluation methods: Data were included if the patient was enrolled in MooseMAP and had a free-text note in the eCare Plan. Data were excluded if the medication-related problem (MRP) or intervention was a general health problem without a valid SNOMED CT code. Data were categorized into MRPs, medication interventions, education, and referrals. The International SNOMED CT browser and pharmacy health information technology (PHIT) value sets were searched; data sets without existing codes were submitted to the appropriate oversight authorities for future inclusion. Data were analyzed using descriptive statistics. ResultsEmerging codes were identified that resulted in 91 recommendations to PHIT for development of new SNOMED CT codes and 113 recommendations to PHIT for inclusion in the PHIT value sets. In total, 66% of MRPs did not have a valid SNOMED CT code, and 78% of MRPs were not included in a PHIT value set. The most prevalent gap in MRP or intervention documentation related to medication use issues. ConclusionIncorporating emerging codes into documentation systems should enable the profession to better communicate value to health care stakeholders.

Building a specialized lexicon for breast cancer clinical trial subject eligibility analysis.

A natural language processing (NLP) application requires sophisticated lexical resources to support its processing goals. Different solutions, such as dictionary lookup and MetaMap, have been proposed in the healthcare informatics literature to identify disease terms with more than one word (multi-gram disease named entities). Although a lot of work has been done in the identification of protein- and gene-named entities in the biomedical field, not much research has been done on the recognition and resolution of terminologies in the clinical trial subject eligibility analysis. In this study, we develop a specialized lexicon for improving NLP and text mining analysis in the breast cancer domain, and evaluate it by comparing it with the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT). We use a hybrid methodology, which combines the knowledge of domain experts, terms from multiple online dictionaries, and the mining of text from sample clinical trials. Use of our methodology introduces 4243 unique lexicon items, which increase bigram entity match by 38.6% and trigram entity match by 41%. Our lexicon, which adds a significant number of new terms, is very useful for matching patients to clinical trials automatically based on eligibility matching. Beyond clinical trial matching, the specialized lexicon developed in this study could serve as a foundation for future healthcare text mining applications.

Harmonized definition of occupational burnout: A systematic review, semantic analysis, and Delphi consensus in 29 countries.

Objective:A consensual definition of occupational burnout is currently lacking. We aimed to harmonize the definition of occupational burnout as a health outcome in medical research and reach a consensus on this definition within the Network on the Coordination and Harmonisation of European Occupational Cohorts (OMEGA-NET).Methods:First, we performed a systematic review in MEDLINE, PsycINFO and Embase (January 1990 to August 2018) and a semantic analysis of the available definitions. We used the definitions of burnout and burnout-related concepts from the Systematized Nomenclature of Medicine Clinical Terms (SNOMED-CT) to formulate a consistent harmonized definition of the concept. Second, we sought to obtain the Delphi consensus on the proposed definition.Results:We identified 88 unique definitions of burnout and assigned each of them to 1 of the 11 original definitions. The semantic analysis yielded a first proposal, further reformulated according to SNOMED-CT and the panelists’ comments as follows: “In a worker, occupational burnout or occupational physical AND emotional exhaustion state is an exhaustion due to prolonged exposure to work-related problems”. A panel of 50 experts (researchers and healthcare professionals with an interest for occupational burnout) reached consensus on this proposal at the second round of the Delphi, with 82% of experts agreeing on it.Conclusion:This study resulted in a harmonized definition of occupational burnout approved by experts from 29 countries within OMEGA-NET. Future research should address the reproducibility of the Delphi consensus in a larger panel of experts, representing more countries, and examine the practicability of the definition.

The Next EPISOD: Trends in Utilization of Endoscopic Sphincterotomy for Sphincter of Oddi Dysfunction from 2010-2019

For years, the endoscopic management of the disorder formerly known as Type III Sphincter of Oddi Dysfunction (SOD) had been controversial. In 2013, the results of the Evaluating Predictors and Interventions in Sphincter of Oddi Dysfunction (EPISOD) trial demonstrated that there was no benefit associated with endoscopic sphincterotomy for patients with Type III SOD. We aimed to assess the utilization of endoscopic sphincterotomy for patients with SOD in a large population database from 2010-2019. We searched a large electronic health record (EHR)-based dataset incorporating over 300 individual hospitals in the United States (Explorys, IBM Watson health, Armonk, NY). Using Systematized Nomenclature of Medicine Clinical Terms (SNOMED-CT) we identified patients with a first-ever diagnosis of "disorder of Sphincter of Oddi" annually from 2010-2019. Subclassification of SOD types was not feasible using SNOMED-CT codes. Stratified by year, we identified the proportion of patients with newly-diagnosed SOD undergoing endoscopic sphincterotomy and those receiving newly-prescribed medical therapy. A total of 39,950,800 individual patients were active in the database with 7,750 index diagnoses of SOD during the study period. The incidence rates of SOD increased from 2.4 to 12.8 per 100,000 persons from 2010-2019 (P < .001). In parallel, there were reductions in the rates of biliary (34.3% to 24.5%) and pancreatic sphincterotomy (25% to 16.4%), respectively (P < .001). Sphincter of Oddi manometry (SOM) was infrequently utilized, <20 times in any given year, throughout the study duration. There were no significant increases in new prescriptions for TCAs, nifedipine, or vasodilatory nitrates. Among a wide range of practice settings which do not utilize routine SOM, a sudden and sustained decrease in rates of endoscopic sphincterotomy for newly-diagnosed SOD was observed beginning in 2013. These findings highlight the critical importance of high-quality, multi-center, randomized controlled trials in endoscopy to drive evidence-based changes in real-world clinical practice.

S0862 Increased Prevalence of Dermatitis Herpetiformis Among Patients With IBD Without Concomitant Celiac Disease: Results From a Population-Based Study

INTRODUCTION: Dermatitis herpetiformis (DH) is an autoimmune eruption of pruritic inflammatory papules and vesicles that occur in a grouped arrangement on different parts of the body. It is characterized by granular deposits of immunoglobulin A (IgA) within the dermal papillae on immunofluorescence. Previous case studies (Alonso-Llamazares et al) and case reports have described an association between DH and ulcerative colitis, possibly arising due to an increased permeability of intestinal mucosal barrier in inflammatory bowel disease (IBD) that allows antigen to circulate in the blood and triggering IgA antibodies. Using a large database, we sought to describe the epidemiology and risk of DH in IBD patients. METHODS: We used a commercial database (Explorys Inc, Cleveland, OH), an aggregate of Electronic Health Record data from 26 US healthcare systems. We identified a cohort of patients with IBD, celiac disease and a diagnosis of DH between June 2015 and 2020. Patients were identified based on a Systemized Nomenclature of Medicine Clinical Terms. We calculated the prevalence of DH in patients with IBD, with celiac, general population, and in individuals with neither IBD nor celiac which served as controls. RESULTS: Out of the 39,212,680 patients active from 2015 to 2020, we identified a total of 5,240 patients with DH (0.013%), 280,460 patients with IBD (0.71%), and 115,020 patients with celiac disease (0.29%). Among those with DH, there were 1290 patients diagnosed with celiac disease (without IBD), 120 patients with IBD (without CD), 60 patients with both celiac and IBD, and 3770 patients with neither celiac nor IBD (control group). The prevalence of DH was 1.12% in celiac disease (without IBD) and 0.043% in IBD (without CD). The prevalence of DH among those without celiac nor IBD (in the control group) was 0.0096%. The risk of DH was higher in celiac [OR 116.6 (109.4–124.2)] and in IBD [OR 4.41 (3.68–5.29)] compared to individuals with neither IBD nor celiac. In the cohort with IBD, risk of DH was higher in females compared to males [OR 3.06 (1.77–5.30)], in elderly patients compared to adults aged 18–65 [4.0 (2.34–6.84)], and in Caucasians compared to non-Caucasians (OR 25.0 [12.7–49.3]). CONCLUSION: Using a large population database, we described the epidemiology and risk of DH in IBD patients. We found that the risk of DH is increased in patients with IBD, consistent with prior case series. Further studies are needed to confirm this association and elucidate the mechanism behind this association.Table 1.: Odd’s ratio comparing the prevalence of dermatitis herpetiformis in celiac disease and in IBD to patients with DH without celiac or IBDTable 2.: Gender-, Age- and Race-Based Prevalence of dermatitis herpetiformis in individuals with IBD in the United States between 2015 and 2020

S0673 Decreasing Prevalence of Colectomy for Ulcerative Colitis Coincides With Increased Utilization of Biologic Medications: A Temporal Analysis From 2000-2019

INTRODUCTION: Ulcerative colitis (UC) treatment has changed significantly over the past 20 years with biologics initiated earlier. Recent reports suggest that early use of biologics may decrease colectomy rates. Our study investigates the trends of colectomy and biologic use UC patients from 2000 to 2019. METHODS: We used a commercial database (Explorys Inc, Cleveland, OH), which includes electronic health record data from 26 major integrated US healthcare systems from 2000 to 2019. Using Systematized Nomenclature of Medicine Clinical Terms, we identified all patients (age >18 years) with UC. The primary outcome was to evaluate the prevalence of UC colectomy and biologic utilization over 2 decades as well as compare these rates with linear regression. We also performed a multi-regression analysis. The biologic group included anti-TNFs, anti-integrin, and anti-IL12,23. RESULTS: Of 61,592,650 patients in the database, we identified 146,430 patients with UC between 2000 and 2019, of whom 15,020 (10.2%) had colectomy and 10,050 (6.8%) patients were treated with biologics, respectively. Over 2 decades, the prevalence of colectomy decreased from 10.8% in 2000 to 2.1% in 2019. This decline was associated with a linear increase in the prevalence of biologic medication utilization in UC from 0.5% in 2000 to 12.8% in 2019, (P < 0.001). After adjusting for other therapies including mesalamine, corticosteroids, and thiopurines, biologics were inversely related to colectomy, P < 0.001, respectively. Meanwhile Mesalamine and colectomy did not have an inverse relation, P < 0.001. CONCLUSION: Colectomy rates have declined over the past 20 years with increased utilization of biologics. This is the largest study utilizing a population-based approach and is consistent with the results of smaller cohort studies that demonstrated declining UC colectomy rates due to biologics.Figure 1.: The trend of colectomy and biologic use prevalence over 2 decades.Figure 2.: The linear regression analysis of colectomy and biologic use prevalence over 2 decades.

Using Systematized Nomenclature of Medicine clinical term codes to assign histological findings for prostate biopsies in the Gauteng province, South Africa: Lessons learnt.

BackgroundProstate cancer (PCa) is a leading male neoplasm in South Africa.ObjectiveThe aim of our study was to describe PCa using Systemized Nomenclature of Medicine (SNOMED) clinical terms codes, which have the potential to generate more timely data.MethodsThe retrospective study design was used to analyse prostate biopsy data from our laboratories using SNOMED morphology (M) and topography (T) codes where the term ’prostate’ was captured in the narrative report. Using M code descriptions, the diagnosis, sub-diagnosis, sub-result and International Classification of Diseases for Oncology (ICD-O-3) codes were assigned using a lookup table. Topography code descriptions identified biopsies of prostatic origin. Lookup tables were prepared using Microsoft Excel and combined with the data extracts using Access. Contingency tables reported M and T codes, diagnosis and sub-diagnosis frequencies.ResultsAn M and T code was reported for 88% (n = 22 009) of biopsies. Of these, 20 551 (93.37%) were of prostatic origin. A benign diagnosis (ICD-O-3:8000/0) was reported for 10 441 biopsies (50.81%) and 45.26% had a malignant diagnosis (n = 9302). An adenocarcinoma (8140/3) sub-diagnosis was reported for 88.16% of malignant biopsies (n = 8201). An atypia diagnosis was reported for 760 biopsies (3.7%). Inflammation (39.03%) and hyperplasia (20.82%) were the predominant benign sub-diagnoses.ConclusionOur study demonstrated the feasibility of generating PCa data using SNOMED codes from national laboratory data. This highlights the need for extending the results of our study to a national level to deliver timeous monitoring of PCa trends.

The 2019 National Natural language processing (NLP) Clinical Challenges (n2c2)/Open Health NLP (OHNLP) shared task on clinical concept normalization for clinical records.

The 2019 National Natural language processing (NLP) Clinical Challenges (n2c2)/Open Health NLP (OHNLP) shared task track 3, focused on medical concept normalization (MCN) in clinical records. This track aimed to assess the state of the art in identifying and matching salient medical concepts to a controlled vocabulary. In this paper, we describe the task, describe the data set used, compare the participating systems, present results, identify the strengths and limitations of the current state of the art, and identify directions for future research. Participating teams were provided with narrative discharge summaries in which text spans corresponding to medical concepts were identified. This paper refers to these text spans as mentions. Teams were tasked with normalizing these mentions to concepts, represented by concept unique identifiers, within the Unified Medical Language System. Submitted systems represented 4 broad categories of approaches: cascading dictionary matching, cosine distance, deep learning, and retrieve-and-rank systems. Disambiguation modules were common across all approaches. A total of 33 teams participated in the MCN task. The best-performing team achieved an accuracy of 0.8526. The median and mean performances among all teams were 0.7733 and 0.7426, respectively. Overall performance among the top 10 teams was high. However, several mention types were challenging for all teams. These included mentions requiring disambiguation of misspelled words, acronyms, abbreviations, and mentions with more than 1 possible semantic type. Also challenging were complex mentions of long, multi-word terms that may require new ways of extracting and representing mention meaning, the use of domain knowledge, parse trees, or hand-crafted rules.

PNS162 USING AMBULATORY EMR DATA TO COMPLEMENT MEDICAL CLAIMS DATA FOR PREDICTIVE ANALYTICS APPLICATIONS

Medical claims data has widely been used in studies to derive real world evidence (RWE) about patient medical history. However, RWE based entirely on the medical claims may be insufficient in detecting patients with rare diseases or chronic conditions as it is limited to pre-determined codes to describe diagnoses, prescriptions and procedures. We propose an approach to reduce this limitation by consolidating medical claims with Ambulatory Electronic Medical Records (AEMR) data which comprises rich information from outpatient settings including unstructured medical notes and lab test results. When linked, these records can complement medical claims data in cases where there 1) isn’t a claim code available to describe a given medical condition, 2) where claim codes are inconsistent across ICD-9 and ICD-10 standards, or 3) where a medical condition is best identified through one or more specific lab results. We leverage AEMR data to identify patients with a chronic condition which doesn’t have a corresponding ICD-10 claim code, and is also difficult to distinguish through business rules alone. Our positive cohort, comprised of patients with the chronic condition, was generated using the problem description field and appropriate SNOMED-CT (Systematized Nomenclature of Medicine Clinical Terms) codes from AEMR data. Model features were generated using medical history in claims data for positive and negative cohorts and a Gradient Boosted Tree classifier (XGBOOST) was built to predict this chronic condition. Study sample included 825,473 patients, 75,043 of which were positives. Results revealed that the model had 43% precision at 25% recall level and our model outperformed the rule-based prediction of chronic condition patients which only had a 20% precision at the same recall level. We provide an approach for incorporating AEMR with claims data to address challenges introduced by the lack of comprehensive information in claims data for predictive analytics studies.

Real-World Practice Patterns in the Era of Rectal Indomethacin for Prophylaxis Against Post-ERCP Pancreatitis in a High-Risk Cohort.

The benefit of indomethacin suppositories for prophylaxis against post-ERCP pancreatitis (PEP) in high-risk patients was established in a landmark trial published in 2012. The aims of this study were to measure the adoption of indomethacin prophylaxis in widespread clinical practice, evaluate concurrent trends in pancreatic duct (PD) stent utilization, and estimate the impact of these changes on PEP in a high-risk population. Data were extracted from a commercial database (Explorys, IBM Watson Health, Somers, NY) that aggregates electronic health records from 26 US healthcare systems from 2009 to 2018. Using Systematized Nomenclature of Medicine Clinical Terms, we identified a cohort of patients who underwent endoscopic retrograde cholangiopancreatography (ERCP) and were at high risk for PEP based on narrow criteria. PEP was defined as an emergency department or hospital admission 1-5 days after ERCP with an associated diagnosis of pancreatitis. Twenty six thousand eight hundred twenty ERCPs were performed on this high-risk cohort from 2009 to 2018. The overall PEP rate during the study period was 8.6%. There was no decrease in PEP rates from 2012 to 2018. Beginning in 2012, indomethacin usage increased linearly (P < 0.001), but remained below 50% in 2018. As indomethacin increased, utilization of PD stents declined abruptly from 2013 to 2014 (40.7%-8.5%) and trended to a nadir of 3.0%. Despite its low cost, widespread availability, and level I evidence of benefit in reducing the risk of PEP in high-risk patients, the adoption of rectal indomethacin during ERCP has been slow and the medication continues to be under-utilized. In parallel, the PD stent usage has declined dramatically. The lack of change in PEP rates during the study period could be attributable to the persistent low usage of rectal indomethacin or the decline in PD stent use. Further educational efforts and quality assurance measures are warranted to ensure that rectal indomethacin and PD stent placement are more appropriately used in clinical practice.

Ontology-Based Radiology Teaching File Summarization, Coverage, and Integration.

Radiology teaching file repositories contain a large amount of information about patient health and radiologist interpretation of medical findings. Although valuable for radiology education, the use of teaching file repositories has been hindered by the ability to perform advanced searches on these repositories given the unstructured format of the data and the sparseness of the different repositories. Our term coverage analysis of two major medical ontologies, Radiology Lexicon (RadLex) and Unified Medical Language System (UMLS) Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT), and two teaching file repositories, Medical Imaging Resource Community (MIRC) and MyPacs, showed that both ontologies combined cover 56.3% of terms in the MIRC and only 17.9% of terms in MyPacs. Furthermore, the overlap between the two ontologies (i.e., terms included by both the RadLex and UMLS SNOMED CT) was a mere 5.6% for the MIRC and 2% for the RadLex. Clustering the content of the teaching file repositories showed that they focus on different diagnostic areas within radiology. The MIRC teaching file covers mostly pediatric cases; a few cases are female patients with heart-, chest-, and bone-related diseases. The MyPacs contains a range of different diseases with no focus on a particular disease category, gender, or age group. MyPacs also provides a wide variety of cases related to the neck, face, heart, chest, and breast. These findings provide valuable insights on what new cases should be added or how existent cases may be integrated to provide more comprehensive data repositories. Similarly, the low-term coverage by the ontologies shows the need to expand ontologies with new terminology such as new terms learned from these teaching file repositories and validated by experts. While our methodology to organize and index data using clustering approaches and medical ontologies is applied to teaching file repositories, it can be applied to any other medical clinical data.

Anticoagulation Increases Bleeding Rates in Portal Vein Thrombosis: A National Database Study

Introduction: Liver cirrhosis is being increasingly recognized as a hypercoagulable state, mainly due to disproportionate reduction in antithrombotic factors (protein C, S and anti-thrombin III). Portal vein thrombosis (PVT) is a frequent sequala of liver cirrhosis that can lead to numerous complications and potential exclusion from transplant lists, at least until the resolution of the thrombus. The current evidence for anticoagulation (AC) for PVT in liver cirrhosis is limited to small retrospective studies. Major liver societies recommend limited anticoagulation with enoxaparin based on expert opinion (Category C). We sought to examine the incidence of bleeding after AC in cirrhotic patients with PVT. Methods: Data were obtained from a commercial de-identified database (Explorys, IBM, Inc.) that integrates electronic health records from 27 major integrated U.S. healthcare systems from 1999 to July 2019. Cases were defined as adult patients aged &gt;=18 years having a new Systematized Nomenclature of Medicine Clinical Terms (SNOMED) diagnosis of PVT, had been anticoagulated for the first time following PVT and had experienced bleeding for the first time following AC. Controls were adults who had a diagnosis of PVT and did not get AC. We included older anticoagulants (warfarin and enoxaparin) as well as newer anticoagulants (apixaban, fondaparinux and rivaroxaban). We compared the incidence of bleeding (defined as bleeding from any site) in those with PVT who received AC to those with PVT who did not receive AC. In addition, we also compared the incidence of bleeding between older and newer anticoagulants, and also examined whether there were differences in gender, race, and insurance status for those who bled while on AC. Analysis comprised of calculating odds ratios (OR) and confidence intervals (CI) for the OR. Results: A total of 213,810 patients had liver cirrhosis and out of those, 7,570 (3.5%) patients had PVT. Four hundred and ten cases out of 1,430 patients who received AC bled for the first time whereas 980 cases out of 3,880 patients who did not receive AC bled for the first time. Cases on AC had 1.18 times higher odds of bleeding when compared to controls who did not receive AC (CI = 1.04 - 1.36). Newer AC were less likely to increase bleeding when compared to older AC (OR = 0.6, CI = 0.4 - 0.9). Females were significantly more likely to be first time bleeders on AC when compared to male first-time bleeders on AC (Table 1). However, race and insurance status did not seem to affect bleeding rates (Table 1). Conclusion: Anticoagulation for PVT in liver cirrhosis increases bleeding events. Newer AC were significantly less likely to increase bleeding when compared to older AC. Females were more likely to bleed on newer AC than males, but race and insurance status did not affect bleeding rates. Limitations of the study include the retrospective nature of the analysis that relied on diagnosis coding, and smaller numbers in our subgroup analyses which limits generalizability. Clinicians should be aware of the significant risk of bleeding when prescribing AC, particularly older AC to cirrhotic patients with PVT. Disclosures No relevant conflicts of interest to declare.

879 Post-ERCP Pancreatitis in Solid Organ Transplant Recipients

INTRODUCTION: Post-ERCP pancreatitis (PEP) is the most common post-procedure complication of ERCP with an incidence of 3.5-15%. The prevalence of PEP and the role of immunosuppression in PEP among solid organ transplant (SOT) recipients is not well established. We aimed to study the prevalence of PEP and the effect of immunosuppressants in SOT recipients. METHODS: A retrospective analysis of 55 million individuals was performed using a cloud-based database, IBM Explorys. Explorys aggregates de-identified electronic health record data from 26 health care systems across the US and rounds to the closest 10 for statistical de-identification. PEP was defined as the elevation of lipase level &gt; 500 U/L along with SNOMED CT (Systematized Nomenclature of Medicine Clinical Terms) diagnosis code of acute pancreatitis within 72 hours of ERCP procedure. The prevalence of PEP and the all-cause 30-day re-admission rate after an episode of PEP were calculated for SOT recipients (lung/kidney/heart/liver). Characteristics were compared using univariate chi-square test between SOT and non-transplant patients as well as liver transplant (LT) recipients and non-transplant patients. P &lt; 0.05 was determined as statistically significant. RESULTS: There was no significant difference in the prevalence of PEP (8.03% vs 8.4%, P = 0.676) and re-admission rate (22.2% vs 20.3%, P = 0.645) between SOT recipients and non-transplant patients. Subgroup analysis of liver transplant (LT) recipients revealed a significantly lower rates of PEP (5.66% vs 8.4%, P = 0.002). Compared to the general population, transplant recipients were less likely to be women [Odds ratio OR 0.567, 95% confidence interval CI (0.375 – 0.866), P = 0.008] (Table 1). Among the transplant recipients, individuals with PEP were more likely to be under 50 years [OR 3.179, CI (1.980 - 5.102), P &lt; 0.001]. PEP rates were lower with SOT recipients on steroids [OR 0.240 CI (0.113 - 0.509), P &lt; 0.001] and calcineurin inhibitors [OR 0.078 CI (0.0317 - 0.194), P &lt; 0.001] (Table 2). CONCLUSION: In this population-based study, the prevalence of PEP was not elevated in SOT recipients. Steroids and calcineurin inhibitors were associated with a protective effect against PEP. To our knowledge, this is the largest cohort to report on PEP in SOT recipients. Since population level database limits access to patients’ charts, studies with details on anatomical and peri-operative risk factors of PEP will further enhance our understanding in this specific subset of population.

An examination of the coverage of the SNOMED CT coded nursing problem list subset.

ObjectiveThe purpose of this article is to describe the current nursing problem list subset of Systematized Nomenclature of Medicine Clinical Terms (NPLS) coverage of the American Nurses Association (ANA) recognized standardized nursing terminologies (SNTs) and to identify potential ways to expand and enhance the utility of this list.Materials and MethodsThe study is a cross-sectional exploratory design. We mapped the content of the North American Nursing Diagnosis Association International (NANDA-I) (2018–2020), International Classification for Nursing Practice (ICNP) (2017 AB), Clinical Care Classification (CCC) (2018 AA), and Omaha System (2007AC) terminologies with each other and into NPLS (August 2017 edition) using Unified Medical Language System (UMLS) (release 2018AA) as the intermediary.ResultsWe identified a total of 1470 unique nursing diagnosis concepts across SNTs in UMLS, including 175 in CCC, 840 in ICNP, 244 in NANDA-I, 418 in Omaha System, and 631 in NPLS. The NPLS covers approximately 43% of the 1470 concepts—coverage for SNT content is 90% for CCC, 47% for ICNP, 59% for NANDA-I, and 32% for the Omaha System.Discussion/RecommendationsThe NPLS version 2017 coverage of SNT nursing diagnoses included in the UMLS is incomplete and equivocal. Recommendations: (1) ensure all SNT concepts in the UMLS are represented by SNOMED CT terms, (2) devise a formal strategy of partial matching to further enhance interoperability, (3) add a classification structure to the NPLS to enhance the ease of use and utility of the list, and (4) minimize redundancy within NPLS.

A Model Information Management Plan for Molecular Pathology Sequence Data Using Standards: From Sequencer to Electronic Health Record

Incorporating genetic variant data into the electronic health record (EHR) in discrete computable fashion has vexed the informatics community for years. Genetic sequence test results are typically communicated by the molecular laboratory and stored in the EHR as textual documents. Although text documents are useful for human readability and initial use, they are not conducive for data retrieval and reuse. As a result, clinicians often struggle to find historical gene sequence results on a series of oncology patients within the EHR that might influence the care of the current patient. Second, identification of patients with specific mutation results in the EHR who are now eligible for new and/or changing therapy is not easily accomplished. Third, the molecular laboratory is challenged to monitor its sequencing processes for nonrandom process variation and other quality metrics. A novel approach to address each of these issues is presented and demonstrated. The authors use standard Health Level 7 laboratory result message formats in conjunction with international standards, Systematized Nomenclature of Medicine Clinical Terms and Human Genome Variant Society nomenclature, to represent, communicate, and store discrete gene sequence data within the EHR in a scalable fashion. This information management plan enables the support of the clinician at the point of care, enhances population management, and facilitates audits for maintaining laboratory quality.

Integrating an Ontology of Radiology Differential Diagnosis with ICD-10-CM, RadLex, and SNOMED CT.

An ontology offers a human-readable and machine-computable representation of the concepts in a domain and the relationships among them. Mappings between ontologies enable the reuse and interoperability of biomedical knowledge. We sought to map concepts of the Radiology Gamuts Ontology (RGO), an ontology that links diseases and imaging findings to support differential diagnosis in radiology, to terms in three key vocabularies for clinical radiology: the International Classification of Diseases, version 10, Clinical Modification (ICD-10-CM), the Radiological Society of North America's radiology lexicon (RadLex), and the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT). RGO (version 0.7; Jan 2018) incorporated 16,918 terms (classes) for diseases, interventions, and imaging observations linked by 1782 subsumption (class-subclass) relations and 55,569 causal ("may cause") relations. RGO classes were mapped to RadLex (46,656 classes, version 3.15), SNOMED CT (347,358 classes, version 2018AA), and ICD-10-CM (94,645 classes, version 2018AA) using the National Center for Biomedical Ontology (NCBO) Annotator web service. We identified 1275 exact mappings from RGO to RadLex, 5302 to SNOMED CT, and 941 to ICD-10-CM. RGO terms mapped to one ontology (n = 3401), two ontologies (n = 1515), or all three ontologies (n = 198). The mapped ontologies provide additional terms to support data mining from textual information in the electronic health record. The current work builds on efforts to map RGO to ontologies of diseases and phenotypes. Mappings between ontologies can support automated knowledge discovery, diagnostic reasoning, and data mining.