scholarly journals Interviews with Patients and Providers on Transgender and Gender Nonconforming Health Data Collection in the Electronic Health Record

2017 ◽  
Vol 2 (1) ◽  
pp. 1-7 ◽  
Author(s):  
M.J. Dunne ◽  
Lewis A. Raynor ◽  
Erika K. Cottrell ◽  
William J.A. Pinnock
Keyword(s):  
Data Collection ◽  
Electronic Health Record ◽  
Health Data ◽  
Health Record ◽  
Gender Nonconforming ◽  
Electronic Health ◽  
And Gender

A Migration Methodology from Legacy to New Electronic Health Record based OpenEHR

2019 ◽  
Vol 10 (1) ◽  
pp. 55-75 ◽  
Author(s):  
Fadoua Khennou ◽  
Nour El Houda Chaoui ◽  
Youness Idrissi Khamlichi
Keyword(s):  
Electronic Health Record ◽  
Level Scheme ◽  
Reference Model ◽  
Critical Issue ◽  
Health Data ◽  
Health Record ◽  
Integration Process ◽  
Flexible Modeling ◽  
Health Practitioners ◽  
Electronic Health

Nowadays, having an electronic health record properly adopted by medical bodies is no longer a challenge. In fact, the critical issue for health practitioners is related to the exchange of health data between different institutes. While some existing standards provide interoperability for e-health systems, they still not offer a coherent solution that can be integrated and used easily. In this author, the paper present OpenEHR, a consistent health standard based on the dual-level scheme, which separates the reference model from the archetypes, allowing a flexible modeling of clinical concepts. However, getting into OpenEHR implementation can be very complex. The purpose of this article is to simplify the integration of OpenEHR, by introducing a stepwise methodology of the migration from legacy SQL-based EHR to an interoperable OpenEHR based NoSQL oriented document model. Successful consolidation was achieved through the deployment of metadata and mapping rules in Java environment project, which allowed a practical automation of the interoperability integration process.

scholarly journals Introducing Sexual Orientation and Gender Identity Into the Electronic Health Record

2015 ◽  
Vol 90 (2) ◽  
pp. 154-160 ◽  
Author(s):  
Edward J. Callahan ◽  
Nicole Sitkin ◽  
Hendry Ton ◽  
W. Suzanne Eidson-Ton ◽  
Julie Weckstein ◽  
...  
Keyword(s):  
Sexual Orientation ◽  
Gender Identity ◽  
Electronic Health Record ◽  
Health Record ◽  
Electronic Health ◽  
And Gender

scholarly journals Exploring the potential of online self-reported and routinely collected electronic healthcare record data in self-harm research

2020 ◽  
Author(s):  
◽  
Amanda Marchant
Keyword(s):  
Cohort Study ◽  
Electronic Health Record ◽  
National Survey ◽  
Health Data ◽  
Data Sources ◽  
Health Record ◽  
Healthcare Data ◽  
Research Register ◽  
Self Harm ◽  
Electronic Health

Background:Self-harm is a major public health concern and is a leading cause of death from injury. Reaching participants for self-harm research raises a number of challenges, however an opportunity exists in the use of both the internet for data collection and in the use of routinely collected healthcare data.Aims and objectives:The aim of this project was to explore the potential of both online and routinely collected healthcare data for self-harm research and the way in which these data sources can be brought together.Methods:This thesis represents a series of projects exploring the use of various data sources for self-harm research. The first was the development and piloting of an online platform (SHARE UK) for self-harm research. This website incorporated multiple functions: hosting questionnaires; sign-up for a research register; sign-up for linkage with routinely collected data and uploads to a media databank. Next a national survey was conducted to explore young people’s perspectives on the use of both online and healthcare data for self-harm research. Lastly a population level electronic health record cohort study analysing trends over time and contacts across healthcare services was conducted.Results:Participants engaged well with research online: 498 participants signed up to the SHARE UK platform; of whom 85% signed up for the research register. Sixty-two participants uploaded 95 items to the media databank. Alternative formats are discussed. Only 15% of participants consented for linkage with healthcare data. A total of 2,733 young people aged 10-24 who self-harm completed the national survey. Results demonstrated that the necessity for participants to give their address for linkage poses a significant barrier. Opinions around the use of Big Data, encompassing social media, marketing and health data are explored.A total of 937,697 individuals aged 10-24 provided 5,269,794 person years of data from 01.01.2003 to 20.09.2015 to the electronic health record cohort study. Self-harm incidence was highest in primary care. Males preferentially present to emergency departments. Male are less likely than females to be admitted following attendance. This difference persists in the youngest age groups and for self-poisoning. Analysis supports the importance of non-specialist services.Conclusions:This thesis has explored both online and routinely collected healthcare data and their utility for self-harm research, exploring participant views and issues via a national survey. An online platform for self-harm research was successfully piloted and issues identified. This series of projects explores possibilities for future self-harm research. The use of multiple data sources allows research to represent both those in the community and those presenting to healthcare settings, lowering many of the barriers to participating in self-harm research. The future utility of the SHARE UK platform through its collaboration with the Adolescent Mental Health Data Platform (ADP) is discussed. Results of this series of projects will be used to inform the development of this platform with lessons learnt from the pilot addressed and findings from both the national survey and the electronic health record cohort study informing and shaping future research.

Customization of electronic health record (EHR) to implement meaningful use for quality improvement (QI).

2013 ◽  
Vol 31 (31_suppl) ◽  
pp. 246-246
Author(s):  
Laura M. Miller ◽  
Bridgette Heard ◽  
Kendall Howard ◽  
Pankaj Kumar
Keyword(s):  
Data Collection ◽  
Electronic Health Record ◽  
Financial Incentive ◽  
Meaningful Use ◽  
Electronic Record ◽  
Stage Ii ◽  
Accurate Information ◽  
Health Record ◽  
Care Providers ◽  
Electronic Health

246 Background: Meaningful Use is a government program that encourages providers to use an electronic health record (EHR) for QI. The goals of MU are to have complete and accurate information in the patient’s electronic record and share that information with other care providers to improve the quality of patient care and avoid duplication of services. The MU program is divided into 3 stages. Providers can earn incentive bonuses for successfully reporting on MU criteria set forth by CMS. There are incentive bonuses for each year until 2015 when penalties for non-reporting are assessed. Stage I has 20 criteria to report on with thresholds for 11 of the criteria. In stage II and III those thresholds will increase. When using an EHR, user efficiency is particularly important. Our goal was to collect MU data by facilitating efficient workflow and taking the documentation burden off the providers. Methods: We identified the MU criteria that required data collection. Some criteria required one time patient data; others involved collecting data at each patient visit. Committees were formed. Processes and responsible staff were identified. We customized features in our EHR to maximize efficiency for the staff collecting the data. We used reports to audit compliance with data collection. Results: We successfully met and reported all 20 Meaningful Use criteria for 16 providers in 2012 and are on track to meet all criteria again in 2013. 11 criteria had measureable thresholds. The average threshold for the 11 measures is 54.5%; our average for the 16 providers for those 11 measures is 86.8%. We collected $288,000 in incentive money for 2013. Since most of the data collection is done by staff, physician documentation is minimal. Conclusions: Customization of EHR allowed us to collect MU data efficiently, obtain the financial incentive in 2012 and helped us get ready for stage II of data collection.

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