the international council on medical & care compunetics


December, 2014

data mining

Pharmacovigilance Using Clinical Notes

LePendu P et al, Clinical Pharmacology & Therapeutics, 2013

With increasing adoption of electronic health records (EHRs), there is an opportunity to use the free-text portion of EHRs for pharmacovigilance. We present novel methods that annotate the unstructured clinical notes and transform them into a deidentified patient–feature matrix encoded using medical terminologies. We demonstrate the use of the resulting high-throughput data for detecting drug–adverse event associations and adverse events associated with drug–drug interactions.
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13 April 2013 | No Comments »
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Chapter 13: Mining Electronic Health Records in the Genomics Era

Denny JC. PLoS Comput Biol, 8(12)

The combination of improved genomic analysis methods, decreasing genotyping costs, and increasing computing resources has led to an explosion of clinical genomic knowledge in the last decade. Similarly, healthcare systems are increasingly adopting robust electronic health record (EHR) systems that not only can improve health care, but also contain a vast repository of disease and treatment data that could be mined for genomic research. Indeed, institutions are creating EHR-linked DNA biobanks to enable genomic and pharmacogenomic research, using EHR data for phenotypic information.
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4 January 2013 | No Comments »
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Mining electronic health records: towards better research applications and clinical care

Jensen PB et al, Nature reviews. Genetics, 13(6)

Clinical data describing the phenotypes and treatment of patients represents an underused data source that has much greater research potential than is currently realized. Mining of electronic health records (EHRs) has the potential for establishing new patient-stratification principles and for revealing unknown disease correlations.
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30 May 2012 | No Comments »
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Studying infant mortality rate: a data mining approach

Chattopadhyay S et al, Health and Technology, 1(1)

The World Health Organization (WHO) uses a large number of health predicators to measure a country’s overall health status. Among many, Infant Mortality Rate (IMR) is considered to be one important. Current literature describes the importance of these predictors in a much segregated manner. Also, its interrelationships are underexplored. This paper describes a framework for mining the hidden relationships of some predictors, such as (i) Population Annual Growth Rate (PAG), (ii) Total Fertility Rate (TFR), (iii) General Government Expenditure (GGE), (iv) Social Security Expenditure (SSE), (v) Total Expenditure on Health (THE), (vi) Access of Drinking Water (ADW), and (vii) Access to Basic Sanitation (ABS) with IMR with the help of Quantitative Association Rule (QAR) mining technique.
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4 September 2011 | No Comments »
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Data Mining Approach Shows Promise in Detecting Unexpected Drug Interactions

Hampton T. JAMA, 306(2)

Up to 1 million patients in the United States may be taking 2 medications that can lead to unexpected increases in blood glucose levels when used simultaneously. Data mining techniques have revealed that the combination of the antidepressant paroxetine and the cholesterol-lowering medication pravastatin may cause this adverse effect (Tatonetti NP et al. Clin Pharmacol Ther. doi: 10.1038/clpt.2011.83 [published online ahead of print May 25, 2011]).
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13 July 2011 | No Comments »
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Social Web mining and exploitation for serious applications: Technosocial Predictive Analytics and related technologies for public health, environmental and national security surveillance

Kamel Boulos MN et al, Computer Methods and Programs in Biomedicine,100(1)

This paper explores Technosocial Predictive Analytics (TPA) and related methods for Web “data mining” where users’ posts and queries are garnered from Social Web (”Web 2.0″) tools such as blogs, micro-blogging and social networking sites to form coherent representations of real-time health events.
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10 July 2011 | No Comments »
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Data-mining case tests boundaries of medical privacy

Woodward C. CMAJ, 183(6)

Hippocrates’ ancient oath to keep secrets sacred between physician and patient is having a rough time of it in the modern age as drug companies, governments and insurers dip into databases rich with personal medical information.
Just how accessible these records should be is a question coming before the United States Supreme Court.
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19 June 2011 | No Comments »
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Bias associated with mining electronic health records

Hripcsak G et al, Journal of Biomedical Discovery and Collaboration, 6

Large-scale electronic health record research introduces biases compared to traditional manually curated retrospective research. We used data from a community-acquired pneumonia study for which we had a gold standard to illustrate such biases. The challenges include data inaccuracy, incompleteness, and complexity, and they can produce in distorted results. We found that a naïve approach approximated the gold standard, but errors on a minority of cases shifted mortality substantially.
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19 June 2011 | No Comments »
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Computer-assisted update of a consumer health vocabulary through mining of social network data

Doing-Harris KM, Zeng-Treitler Q. J Med Internet Res, 13(2)

Consumer health vocabularies (CHVs) have been developed to aid consumer health informatics applications. This purpose is best served if the vocabulary evolves with consumers’ language.

Our objective was to create a computer assisted update (CAU) system that works with live corpora to identify new candidate terms for inclusion in the open access and collaborative (OAC) CHV.
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29 May 2011 | No Comments »
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Electronic health records: implications for drug discovery

Yao L et al, Drug Discovery Today, 2011

Electronic health records (EHRs) have increased in popularity in many countries. Pushed by legal mandates, EHR systems have seen substantial progress recently, including increasing adoption of standards, improved medical vocabularies and enhancements in technical infrastructure for data sharing across healthcare providers. Although the progress is directly beneficial to patient care in a hospital or clinical setting, it can also aid drug discovery.
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25 May 2011 | No Comments »
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Development of a personal electronic health record card in the United Kingdom

Rybynok VO et al, Conf Proc IEEE Eng Med Biol Soc, 2010

In most emergency situations, health professionals rely on patients to provide information about their medical history. However, in some cases patients might not be able to communicate this information, and in most countries, including the UK an on-line integrated patient record system has not been adopted. Therefore, in order to address this issue the ongoing project MyCare Card (MyC(2), www.myc2.org) has been established. The aim of this project is to design, implement and evaluate a prototype patient held electronic health record card.
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10 April 2011 | No Comments »
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Review of Extracting Information From the Social Web for Health Personalization

Fernandez-Luque L et al, J Med Internet Res, 13(1)

In recent years the Web has come into its own as a social platform where health consumers are actively creating and consuming Web content. Moreover, as the Web matures, consumers are gaining access to personalized applications adapted to their health needs and interests. The creation of personalized Web applications relies on extracted information about the users and the content to personalize. The Social Web itself provides many sources of information that can be used to extract information for personalization apart from traditional Web forms and questionnaires.
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29 January 2011 | No Comments »
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Application of data mining to the identification of critical factors in patient falls using a web-based reporting system

Lee T et al, International Journal of Medical Informatics, 2010

The implementation of an information system has become a trend in healthcare institutions. How to identify variables related to patient safety among accumulated data has been viewed as a main issue. The purpose of this study was to identify critical factors related to patient falls through the application of data mining to available data through a hospital information system.
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8 November 2010 | No Comments »
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An ontology-based measure to compute semantic similarity in biomedicine

Proper understanding of textual data requires the exploitation and integration of unstructured and heterogeneous clinical sources, healthcare records or scientific literature, which are fundamental aspects in clinical and translational research. The determination of semantic similarity between word pairs is an important component of text understanding that enables the processing, classification and structuring of textual resources. In the past, several approaches for assessing word similarity by exploiting different knowledge sources (ontologies, thesauri, domain corpora, etc.) have been proposed. Some of these measures have been adapted to the biomedical field by incorporating domain information extracted from clinical data or from medical ontologies (such as MeSH or SNOMED CT).
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19 September 2010 | No Comments »
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Data extraction from a semi-structured electronic medical record system for outpatients: a model to facilitate the access and use of data for quality control and research

Kristianson KJ et al, Health Informatics Journal, 15(4)

The use of clinical data from electronic medical records (EMRs) for clinical research and for evaluation of quality of care requires an extraction process. Many efforts have failed because the extracted data seemed to be unstructured, incomplete and ridden by errors. We have developed and tested a concept of extracting semi-structured EMRs (Journal III, Profdoc) data from 776 diabetes patients in a general practice clinic over a 5 year period. We used standard database management techniques commonly applied in clinical research in the pharmaceutical industry to clean up the data and make the data available for statistical analysis.
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1 August 2010 | No Comments »
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THE-MUSS: Mobile u-health service system

Han D, et al, Computer Methods and Programs in Biomedicine, 97(2)

In this paper, we introduce a mobile u-health service system called THE-MUSS. THE-MUSS supports the development and running of u-health services with functions, modules, and facilities that are commonly required for various mobile u-health services. Aiming to achieve reusability and evolvability design goals, basic modules to support bio-signal capturing, processing, analysis, diagnosis, and feedback are developed and stacked in the layered architecture of THE-MUSS.
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19 April 2010 | No Comments »
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Distribution of Problems, Medications and Lab Results in Electronic Health Records: The Pareto Principle at Work

Wright A, Bates DW, Applied Clinical Informatics, 1(1)

Many natural phenomena demonstrate power-law distributions, where very common items predominate. Problems, medications and lab results represent some of the most important data elements in medicine, but their overall distribution has not been reported.
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8 April 2010 | No Comments »
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Online resources of cancer data: barriers, benefits and lessons

Gadaleta, Emanuela et al, Briefings in Bioinformatics, 2010

With advances in high-throughput techniques, the volume of data generated has resulted in the creation of a plethora of resources for the cancer research community. However, a key factor in the utility, sustainability and future use of a novel resource lies in its ability to allow for data sharing and to be interoperable with major international cancer research efforts.
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31 March 2010 | No Comments »
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Clinical data mining and research in the allergy office

Dalan, Dan, Current Opinion in Allergy and Clinical Immunology, 2010

Purpose of review:
More data are anticipated from the expected increase in use of electronic health records (EHRs). Upcoming initiatives require reporting of quality measures, meaningful use of clinical decision support, alert systems, and pharmacovigilance – knowledge resulting through use of EHRs. Data mining is a new tool that will help us manage information and derive knowledge from these data, and is a part of evolving new disciplines of informatics and knowledge management.
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26 February 2010 | No Comments »
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The EU-ADR project: preliminary results and perspective

Trifiro, Gianluca et al, Detection and Prevention of Adverse Drug Events - Information Technologies and Human Factors, 2009

The EU-ADR project aims to exploit different European electronic healthcare records (EHR) databases for drug safety signal detection. In this paper we describe the project framework and the preliminary results.

As first step we created a ranked list of the events that are deemed to be important in pharmacovigilance as mining on all possible events was considered to unduly increase the number of spurious signals. All the drugs that are potentially associated to these events will be detected via data mining techniques. Data sources are eight 8 databases in four countries (Denmark, Italy, the Netherlands, and the United Kingdom) that are virtually linked through harmonisation of input data followed by local elaboration of input data through custom-built software (Jerboa©). All the identified drug-event associations (signals) will be thereafter biologically substantiated and epidemiologically validated. To date, only Upper gastrointestinal bleeding (UGIB) event has been used to test the ability of the system in signal detection.
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6 January 2010 | No Comments »
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