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1.
Biomed Res Int ; 2015: 801436, 2015.
Article in English | MEDLINE | ID: mdl-26539525

ABSTRACT

The Electronic Health Records for Clinical Research (EHR4CR) project aims to develop services and technology for the leverage reuse of Electronic Health Records with the purpose of improving the efficiency of clinical research processes. A pilot program was implemented to generate evidence of the value of using the EHR4CR platform. The user acceptance of the platform is a key success factor in driving the adoption of the EHR4CR platform; thus, it was decided to evaluate the user satisfaction. In this paper, we present the results of a user satisfaction evaluation for the EHR4CR multisite patient count cohort system. This study examined the ability of testers (n = 22 and n = 16 from 5 countries) to perform three main tasks (around 20 minutes per task), after a 30-minute period of self-training. The System Usability Scale score obtained was 55.83 (SD: 15.37), indicating a moderate user satisfaction. The responses to an additional satisfaction questionnaire were positive about the design of the interface and the required procedure to design a query. Nevertheless, the most complex of the three tasks proposed in this test was rated as difficult, indicating a need to improve the system regarding complicated queries.


Subject(s)
Biomedical Research/methods , Clinical Trials as Topic/methods , Electronic Health Records , Humans , Program Evaluation , Task Performance and Analysis
2.
Stud Health Technol Inform ; 210: 506-10, 2015.
Article in English | MEDLINE | ID: mdl-25991199

ABSTRACT

INTRODUCTION: In the last few years much work has been conducted in creating systems that support clinical trials for example by utilizing electronic health record data. One of these endeavours is the Electronic Health Record for Clinical Research project (EHR4CR). An unanswered question that the project aims to answer is which data elements are most commonly required for patient recruitment. METHODS: Free text eligibility criteria from 40 studies were analysed, simplified and elements were extracted. These elements where then added to an existing inventory of data elements for protocol feasibility. RESULTS: We simplified and extracted data elements from 40 trials, which resulted in 1170 elements. From these we created an inventory of 150 unique data elements relevant for patient identification and recruitment with definitions and referenced codes to standard terminologies. DISCUSSION: Our list was created with expertise from pharmaceutical companies. Comparisons with related work shows that identified concepts are similar. An evaluation of the availability of these elements in electronic health records is still ongoing. Hospitals that want to engage in re-use of electronic health record data for research purposes, for example by joining networks like EHR4CR, can now prioritize their effort based on this list.


Subject(s)
Clinical Trials as Topic/methods , Data Mining/methods , Electronic Health Records/classification , Electronic Health Records/statistics & numerical data , Eligibility Determination/methods , Patient Selection , Databases, Factual , Europe , Terminology as Topic
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