Open Source, Open Standards, and Health Care Information Systems

Jeremy C Wyatt,Carl J Reynolds

doi:10.2196/jmir.1521

Abstract

Recognition of the improvements in patient safety, quality of patient care, and efficiency that health care information systems have the potential to bring has led to significant investment. Globally the sale of health care information systems now represents a multibillion dollar industry. As policy makers, health care professionals, and patients, we have a responsibility to maximize the return on this investment. To this end we analyze alternative licensing and software development models, as well as the role of standards. We describe how licensing affects development. We argue for the superiority of open source licensing to promote safer, more effective health care information systems. We claim that open source licensing in health care information systems is essential to rational procurement strategy.

Highlights

It is noted that the task of importing training, testing and forecasting data sets from EMR systems in the machine learning environment is not so trivial for a number of reasons discussed in the study
We consider the data of clinical, laboratory studies of 1,469 women who were previously stored in the OpenEMR system
The development of the machine learning model was implemented in the R free software environment, using the mlr package

Summary

SYSTEMS OF ELECTRONIC MEDICAL RECORDS

The prospects of open source electronic medical records software and free systems for developing countries and countries with financial difficulties were discussed in the works of F. Approaches to the implementation of open source systems of electronic medical records, especially OpenEMR, OpenMRS and OpenDental, in the health care system of Ukraine have been studied, as well as methods of integration of these systems with other software of medical direction, developed by authors in recent years [8], [9], [6], [5]. The goal of the work is to develop mathematical, software for the development of models of machine learning in medicine, based on the use of systems of electronic medical records with open source and means of machine learning. ...,a i p (called attributes) and output data c i which is an attribute of the class

Let the vector string aj

We calculate variations of

Conclusions