Primary ventral and incisional hernias: comprehensive review.

Background: Primary ventral and incisional hernias are frequent conditions that impact the quality of life of patients. Surgical techniques for ventral hernia repair are constantly evolving and abdominal wall surgery has turned into a highly specialized field.

Methods: This is a narrative review of the most recent and relevant literature on the treatment of primary ventral and incisional hernias performed by eight experts in ventral hernia surgery from across the world and includes review of classification systems, preoperative measures, descriptions of surgical techniques, and postoperative complications.

Development and evaluation of an EHR-based computable phenotype for identification of pediatric Crohn's disease patients in a National Pediatric Learning Health System.

Objectives: To develop and evaluate the classification accuracy of a computable phenotype for pediatric Crohn's disease using electronic health record data from PEDSnet, a large, multi-institutional research network and Learning Health System.

Study Design: Using clinician and informatician input, algorithms were developed using combinations of diagnostic and medication data drawn from the PEDSnet clinical dataset which is comprised of 5.6 million children from eight U.

Design and Refinement of a Data Quality Assessment Workflow for a Large Pediatric Research Network.

Background: Clinical data research networks (CDRNs) aggregate electronic health record data from multiple hospitals to enable large-scale research. A critical operation toward building a CDRN is conducting continual evaluations to optimize data quality. The key challenges include determining the assessment coverage on big datasets, handling data variability over time, and facilitating communication with data teams.

A Data Element-Function Conceptual Model for Data Quality Checks.

Introduction: In aggregate, existing data quality (DQ) checks are currently represented in heterogeneous formats, making it difficult to compare, categorize, and index checks. This study contributes a data element-function conceptual model to facilitate the categorization and indexing of DQ checks and explores the feasibility of leveraging natural language processing (NLP) for scalable acquisition of knowledge of common data elements and functions from DQ checks narratives.

Methods: The model defines a "data element", the primary focus of the check, and a "function", the qualitative or quantitative measure over a data element.

Predicting Causes of Data Quality Issues in a Clinical Data Research Network.

Clinical data research networks (CDRNs) invest substantially in identifying and investigating data quality problems. While identification is largely automated, the investigation and resolution are carried out manually at individual institutions. In the PEDSnet CDRN, we found that only approximately 35% of the identified data quality issues are resolvable as they are caused by errors in the extract-transform-load (ETL) code.

A Comparison of Data Quality Assessment Checks in Six Data Sharing Networks.

Objective: To compare rule-based data quality (DQ) assessment approaches across multiple national clinical data sharing organizations.

Methods: Six organizations with established data quality assessment (DQA) programs provided documentation or source code describing current DQ checks. DQ checks were mapped to the categories within the data verification context of the harmonized DQA terminology.

Retrospective Analysis of Candida-related Conditions in Infancy and Early Childhood Caries.

Purpose: The purpose of this study was to assess whether there is an association between oral thrush or other Candida-related conditions in infancy and early childhood caries (ECC) diagnosed by pediatricians.

Methods: We conducted a retrospective cohort study using electronic health records from six national children's hospitals that participate in the PEDSnet research network. There were 1,012,668 children with a visit at ages one to 12 months and another visit at ages 13 to 71 months.

A longitudinal analysis of data quality in a large pediatric data research network.

Objective: PEDSnet is a clinical data research network (CDRN) that aggregates electronic health record data from multiple children's hospitals to enable large-scale research. Assessing data quality to ensure suitability for conducting research is a key requirement in PEDSnet. This study presents a range of data quality issues identified over a period of 18 months and interprets them to evaluate the research capacity of PEDSnet.

Multisite Evaluation of a Data Quality Tool for Patient-Level Clinical Data Sets.

Introduction: Data quality and fitness for analysis are crucial if outputs of analyses of electronic health record data or administrative claims data should be trusted by the public and the research community.

Methods: We describe a data quality analysis tool (called Achilles Heel) developed by the Observational Health Data Sciences and Informatics Collaborative (OHDSI) and compare outputs from this tool as it was applied to 24 large healthcare datasets across seven different organizations.

Results: We highlight 12 data quality rules that identified issues in at least 10 of the 24 datasets and provide a full set of 71 rules identified in at least one dataset.

Challenges in clinical natural language processing for automated disorder normalization.

Background: Identifying key variables such as disorders within the clinical narratives in electronic health records has wide-ranging applications within clinical practice and biomedical research. Previous research has demonstrated reduced performance of disorder named entity recognition (NER) and normalization (or grounding) in clinical narratives than in biomedical publications. In this work, we aim to identify the cause for this performance difference and introduce general solutions.

Crowdsourcing in biomedicine: challenges and opportunities.

The use of crowdsourcing to solve important but complex problems in biomedical and clinical sciences is growing and encompasses a wide variety of approaches. The crowd is diverse and includes online marketplace workers, health information seekers, science enthusiasts and domain experts. In this article, we review and highlight recent studies that use crowdsourcing to advance biomedicine.

Scaling drug indication curation through crowdsourcing.

Motivated by the high cost of human curation of biological databases, there is an increasing interest in using computational approaches to assist human curators and accelerate the manual curation process. Towards the goal of cataloging drug indications from FDA drug labels, we recently developed LabeledIn, a human-curated drug indication resource for 250 clinical drugs. Its development required over 40 h of human effort across 20 weeks, despite using well-defined annotation guidelines.

Hybrid curation of gene-mutation relations combining automated extraction and crowdsourcing.

Background: This article describes capture of biological information using a hybrid approach that combines natural language processing to extract biological entities and crowdsourcing with annotators recruited via Amazon Mechanical Turk to judge correctness of candidate biological relations. These techniques were applied to extract gene- mutation relations from biomedical abstracts with the goal of supporting production scale capture of gene-mutation-disease findings as an open source resource for personalized medicine.

Results: The hybrid system could be configured to provide good performance for gene-mutation extraction (precision ∼82%; recall ∼70% against an expert-generated gold standard) at a cost of $0.

LabeledIn: cataloging labeled indications for human drugs.

Drug-disease treatment relationships, i.e., which drug(s) are indicated to treat which disease(s), are among the most frequently sought information in PubMed®.

tmBioC: improving interoperability of text-mining tools with BioC.

The lack of interoperability among biomedical text-mining tools is a major bottleneck in creating more complex applications. Despite the availability of numerous methods and techniques for various text-mining tasks, combining different tools requires substantial efforts and time owing to heterogeneity and variety in data formats. In response, BioC is a recent proposal that offers a minimalistic approach to tool interoperability by stipulating minimal changes to existing tools and applications.

BioC interoperability track overview.

BioC is a new simple XML format for sharing biomedical text and annotations and libraries to read and write that format. This promotes the development of interoperable tools for natural language processing (NLP) of biomedical text. The interoperability track at the BioCreative IV workshop featured contributions using or highlighting the BioC format.

Accessing biomedical literature in the current information landscape.

Biomedical and life sciences literature is unique because of its exponentially increasing volume and interdisciplinary nature. Biomedical literature access is essential for several types of users including biomedical researchers, clinicians, database curators, and bibliometricians. In the past few decades, several online search tools and literature archives, generic as well as biomedicine specific, have been developed.

Automatic extraction of drug indications from FDA drug labels.

Extracting computable indications, i.e. drug-disease treatment relationships, from narrative drug resources is the key for building a gold standard drug indication repository.

External pancreatic fistula as a sequel to management of acute severe necrotizing pancreatitis.

Background/aims: External pancreatic fistula (EPF) is a common sequel to surgical or percutaneous intervention for infective complications of acute severe pancreatitis. The present study was aimed at studying the clinical profile, course and outcome of patients with EPF following surgical or percutaneous management of these infective complications.

Methods: A retrospective analysis of clinical data of patients with EPF following intervention (surgical or percutaneous) for acute severe pancreatitis managed between January 1989 and April 2002 recorded on a prospective database was done.

Should laparoscopic cholecystectomy be performed in patients with thick-walled gallbladder?

Background/purpose: Laparoscopic cholecystectomy is the procedure of choice for patients with symptomatic cholelithiasis. This procedure is contraindicated in patients with gall-bladder cancer (GBC) because of fear of dissemination of the disease. One of the findings raising the suspicion of GBC is a thick-walled gallbladder (TWGB).

Extrahepatic portal venous obstruction and obstructive jaundice: approach to management.

Background: Patients with long-standing extrahepatic portal venous obstruction (EHPVO) develop extensive collaterals in the hepatoduodenal ligament as a result of enlargement of the periportal veins. These patients are also prone to develop obstructive jaundice as a result of strictures and/or choledocholithiasis. Surgical management of obstructive jaundice in such patients becomes difficult in the presence of these collaterals.