Comparison of Open-Source Electronic Health Record Systems Based on Functional and User Performance Criteria

Objectives: Open-source Electronic Health Record (EHR) systems have gained importance. The main aim of our research is to guide organizational choice by comparing the features, functionality, and user-facing system performance of the five most popular open-source EHR systems. Methods: We performed qualitative content analysis with a directed approach on recently published literature (2012-2017) to develop an integrated set of criteria to compare the EHR systems. The functional criteria are an integration of the literature, meaningful use criteria, and the Institute of Medicine's functional requirements of EHR, whereas the user-facing system performance is based on the time required to perform basic tasks within the EHR system. Results: Based on the Alexa web ranking and Google Trends, the five most popular EHR systems at the time of our study were OSHERA VistA, GNU Health, the Open Medical Record System (OpenMRS), Open Electronic Medical Record (OpenEMR), and OpenEHR. We also found the trends in popularity of the EHR systems and the locations where they were more popular than others. OpenEMR met all the 32 functional criteria, OSHERA VistA met 28, OpenMRS met 12 fully and 11 partially, OpenEHR-based EHR met 10 fully and 3 partially, and GNU Health met the least with only 10 criteria fully and 2 partially. Conclusions: Based on our functional criteria, OpenEMR is the most promising EHR system, closely followed by VistA. With regards to user-facing system performance, OpenMRS has superior performance in comparison to OpenEMR

Evaluating openEHR for storing computable representations of electronic health record phenotyping algorithms

Electronic Health Records (EHR) are data generated during routine clinical care. EHR offer researchers unprecedented phenotypic breadth and depth and have the potential to accelerate the pace of precision medicine at scale. A main EHR use-case is creating phenotyping algorithms to define disease status, onset and severity. Currently, no common machine-readable standard exists for defining phenotyping algorithms which often are stored in human-readable formats. As a result, the translation of algorithms to implementation code is challenging and sharing across the scientific community is problematic. In this paper, we evaluate openEHR, a formal EHR data specification, for computable representations of EHR phenotyping algorithms.Comment: 30th IEEE International Symposium on Computer-Based Medical Systems - IEEE CBMS 201

ROMOP: a light-weight R package for interfacing with OMOP-formatted electronic health record data.

Objectives:Electronic health record (EHR) data are increasingly used for biomedical discoveries. The nature of the data, however, requires expertise in both data science and EHR structure. The Observational Medical Out-comes Partnership (OMOP) common data model (CDM) standardizes the language and structure of EHR data to promote interoperability of EHR data for research. While the OMOP CDM is valuable and more attuned to research purposes, it still requires extensive domain knowledge to utilize effectively, potentially limiting more widespread adoption of EHR data for research and quality improvement. Materials and methods:We have created ROMOP: an R package for direct interfacing with EHR data in the OMOP CDM format. Results:ROMOP streamlines typical EHR-related data processes. Its functions include exploration of data types, extraction and summarization of patient clinical and demographic data, and patient searches using any CDM vocabulary concept. Conclusion:ROMOP is freely available under the Massachusetts Institute of Technology (MIT) license and can be obtained from GitHub (http://github.com/BenGlicksberg/ROMOP). We detail instructions for setup and use in the Supplementary Materials. Additionally, we provide a public sandbox server containing synthesized clinical data for users to explore OMOP data and ROMOP (http://romop.ucsf.edu)

PatientExploreR: an extensible application for dynamic visualization of patient clinical history from electronic health records in the OMOP common data model.

MotivationElectronic health records (EHRs) are quickly becoming omnipresent in healthcare, but interoperability issues and technical demands limit their use for biomedical and clinical research. Interactive and flexible software that interfaces directly with EHR data structured around a common data model (CDM) could accelerate more EHR-based research by making the data more accessible to researchers who lack computational expertise and/or domain knowledge.ResultsWe present PatientExploreR, an extensible application built on the R/Shiny framework that interfaces with a relational database of EHR data in the Observational Medical Outcomes Partnership CDM format. PatientExploreR produces patient-level interactive and dynamic reports and facilitates visualization of clinical data without any programming required. It allows researchers to easily construct and export patient cohorts from the EHR for analysis with other software. This application could enable easier exploration of patient-level data for physicians and researchers. PatientExploreR can incorporate EHR data from any institution that employs the CDM for users with approved access. The software code is free and open source under the MIT license, enabling institutions to install and users to expand and modify the application for their own purposes.Availability and implementationPatientExploreR can be freely obtained from GitHub: https://github.com/BenGlicksberg/PatientExploreR. We provide instructions for how researchers with approved access to their institutional EHR can use this package. We also release an open sandbox server of synthesized patient data for users without EHR access to explore: http://patientexplorer.ucsf.edu.Supplementary informationSupplementary data are available at Bioinformatics online

EHR requirements

Published requirements for the EHR are principally available via ISO 18308. They are statements defining the generic features necessary in any Electronic Health Record for it to be communicable and complete, retain integrity across systems, countries and time, and be a useful and effective ethico-legal record of care. Examples of requirements are provided in four themes: -EHR functional requirements; Ethical, legal, and security requirements; Clinical requirements; Technical requirements. The main logical building blocks of an EHR are described using the terminology of CEN TC251 ENV13606. Examples are given of the placement of attributes to satisfy contextual and other requirements at the level of specific building blocks. A worked example of the use of the building blocks is given for the request-report cycle for an imaging investigation

Electronic health record standards

Objectives: This paper seeks to provide an overview of the initiatives that are proceeding internationally to develop standards for the exchange of electronic health record (EHR) information between EHR systems.Methods: The paper reviews the clinical and ethico-legal requirements and research background on the representation and communication of EHR data, which primarily originates from Europe through a series of EU funded Health Telematics projects over the post thirteen years. The major concept that underpin the information models and knowledge models are summarised. These provide the requirements and the best evidential basis from which HER communications standards should be developed.Results. The main focus of EHR communications standardisation is presently occurring at a European level, through the Committee for European Normalisation (CEN). The major constructs of the CEN 13606 model ate outlined. Complementary activity is taking place in ISO and in HL7, and some of these efforts are also summarised.Conclusior: There is a strong prospect that a generic EHR interoperability standard can be agreed at a European (and hopefully international) level. Parts of the challenge of EHR i interoperability cannot yet he standardised, because good solutions to the preservation of clinical meaning across heterogeneous systems remain to be explored. Further research and empirical projects are therefore also needed

Confidential genetic testing and electronic health records: A survey of current practices among Huntington disease testing centers

BACKGROUND: Clinical care teams providing presymptomatic genetic testing often employ advanced confidentiality practices for documentation and result storage. However, patient requests for increased confidentiality may be in conflict with the legal obligations of medical providers to document patient care activities in the electronic health record (EHR). Huntington disease presents a representative case study for investigating the ways centers currently balance the requirements of EHRs with the privacy demands of patients seeking presymptomatic genetic testing. METHODS: We surveyed 23 HD centers (53% response rate) regarding their use of the EHR for presymptomatic HD testing. RESULTS: Our survey revealed that clinical care teams and laboratories have each developed their own practices, which are cumbersome and often include EHR avoidance. We found that a majority of HD care teams record appointments in the EHR (91%), often using vague notes. Approximately half of the care teams (52%) keep presymptomatic results of out of the EHR. CONCLUSION: As genetic knowledge grows, linking more genes to late-onset conditions, institutions will benefit from having professional recommendations to guide development of policies for EHR documentation of presymptomatic genetic results. Policies must be sensitive to the ethical differences and patient demands for presymptomatic genetic testing compared to those undergoing confirmatory genetic testing

We are bitter, but we are better off: Case study of the implementation of an electronic health record system into a mental health hospital in England

In contrast to the acute hospital sector, there have been relatively few implementations of integrated electronic health record (EHR) systems into specialist mental health settings. The National Programme for Information Technology (NPfIT) in England was the most expensive IT-based transformation of public services ever undertaken, which aimed amongst other things, to implement integrated EHR systems into mental health hospitals. This paper describes the arrival, the process of implementation, stakeholders' experiences and the local consequences of the implementation of an EHR system into a mental health hospital