Statistical Analysis

OpenClinic GA

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OpenClinic GA is an open source integrated hospital information management system covering management of administrative, financial, clinical, lab, x-ray, pharmacy, meals distribution and other data. Extensive statistical and reporting capabilities.

Features:

Homepage: 
http://sourceforge.net/projects/open-clinic/

EGADSS

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EGADSS (Evidence-based Guideline and Decision Support System) is an open source tool that is designed to work in conjunction with primary care Electronic Medical Record (EMR) systems to provide patient specific point of care reminders in order to aid physicians provide high quality care. EGADSS is designed as a stand alone system that would respond to requests from existing Electronic Medical Records such as Wolf, Med Access, and MedOffIS to provide patient specific clinical guidance based on its internal collection of guidelines.

Homepage: 
http://egadss.sourceforge.net/

ClinStudyWeb

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ClinStudyWeb is designed to provide a flexible infrastructure for managing patient and assay data from clinical studies. It uses a plugin system for study-specific web forms and arbitrarily complex test classifiers, and supports XML import/export.

Homepage: 
http://sourceforge.net/projects/clinstudyweb/

CASE

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The main goal of the Computer Assisted Search for Epidemics (CASE) project is to develop a reliable system that generates warnings when the number of reported cases of a particular infectious disease reaches a level that indicates an unusual or unexpected rate. The system is currently in use at the Swedish Institute for Infectious Disease Control (SMI). It performs daily surveillance using data obtained from the database to which all notifiable diseases are reported in Sweden.

Homepage: 
https://smisvn.smi.se/case/

openCDMS

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The openCDMS project is a community effort to develop a robust, commercial-grade, full-featured and open source clinical data management system for studies and trials. The philosophy behind openCDMS is to enable clinical researchers to manage the full life cycle of their clinical research project, from design through to archiving, without any specialist knowledge of databases or IT systems.

openCDMS provides purpose built visual tools the enable clinical researchers to design, develop, implement, and manage large scale, multi-centre studies and trials quickly and easily.

Homepage: 
http://www.opencdms.org/

ESP

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The Electronic medical record Support for Public health (ESP) project is an automated software application, that analyzes electronic medical record (EMR) data, to identify and report conditions of interest to public health and other agencies.

Homepage: 
http://esphealth.org/

The 'medAdherence' R Package

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Adherence is defined as "the extent to which a person’s behavior coincides with medical or health
advice", which is very important, for both clinical researchers and physicians, to identify the treatment
effect of a specific medication(s).

Homepage: 
http://cran.r-project.org/web/packages/medAdherence/

The 'epiR' R Package

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A package for analysing epidemiological data. Contains functions for directly and indirectly adjusting measures of disease frequency, quantifying measures of association on the basis of single or multiple strata of count data presented in a contingency table, and computing confidence intervals around incidence risk and incidence rate estimates. Miscellaneous functions for use in meta-analysis, diagnostic test interpretation, and sample size calculations.

Homepage: 
http://cran.r-project.org/web/packages/epiR/

The 'epicalc' R Package

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Functions making R easy for epidemiological calculation.

Datasets from Dbase (.dbf), Stata (.dta), SPSS(.sav), EpiInfo(.rec) and Comma separated value (.csv) formats as well as R data frames can be processed to do make several epidemiological calculations.

Homepage: 
http://cran.r-project.org/web/packages/epicalc/

The 'epibasix' R Package

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This package contains elementary tools for analysis of common epidemiological problems, ranging from sample size estimation, through 2x2 contingency table analysis and basic measures of agreement (kappa, sensitivity/specificity).

Appropriate print and summary statements are also written to facilitate interpretation wherever possible.

This package is a work in progress, so any comments or suggestions would be appreciated. Source code is commented throughout to facilitate modification. The target audience includes graduate students in various epi/biostatistics courses.

Homepage: 
http://cran.r-project.org/web/packages/epibasix/

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