scholarly journals Electronic health record (EHR) projects in Canada: participation options for Canadian health librarians

2014 ◽  
Vol 32 (3) ◽  
pp. 137 ◽  
Author(s):  
Sandra Barron ◽  
Sumanjit Manhas
Keyword(s):  
Electronic Health Record ◽  
Research Question ◽  
Grey Literature ◽  
Online News ◽  
Biomedical Literature ◽  
Library Science ◽  
Data Sources ◽  
Health Record ◽  
Canadian Health ◽  
Electronic Health

Research question: What are the major issues in the implementation of electronic health record (EHR) systems in Canada and what competencies can Canadian health librarians bring to their participation in these projects? Data sources: Health informatics and library science databases were searched for EHR literature. Grey literature was located at Canada Health Infoway's website, on provincial and federal government websites, and by searching online news websites. Study selection: The data sources were searched for journal articles, reviews, newspaper articles, government publications, interviews, grey literature, dissertations, editorials, and discussions. Data extraction: Data were extracted from the data sources using search strategies and keywords outlined in Appendix A. Due to the scope and focus of this paper, search terms were selected to emphasize a Canadian context; in particular, a British Columbian perspective in regards to EHR implementation. Results: This paper draws on a body of evidence to discuss EHR implementation issues and health librarian involvement in Canada. There is a growing body of research in the American biomedical literature about health librarian participation in EHR implementation but little in the Canadian health literature. Conclusion: This is the first paper of its kind that proposes new roles for Canadian health librarians in EHR implementation. Health librarians’ expertise in organizing and retrieving information makes them ideally suited for providing evidence-based medicine or consumer health information embedded directly in EHRs. Further research is needed to demonstrate the value of health librarians on EHR project teams.

scholarly journals Approaches for combining primary care electronic health record data from multiple sources: a systematic review of observational studies

BMJ Open ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. e037405
Author(s):  
Daniel Dedman ◽  
Melissa Cabecinha ◽  
Rachael Williams ◽  
Stephen J W Evans ◽  
Krishnan Bhaskaran ◽  
...  
Keyword(s):  
Systematic Review ◽  
Primary Care ◽  
Electronic Health Record ◽  
Observational Studies ◽  
Meta Analysis ◽  
Data Sources ◽  
Health Record ◽  
Two Stage ◽  
One Stage ◽  
Electronic Health

ObjectiveTo identify observational studies which used data from more than one primary care electronic health record (EHR) database, and summarise key characteristics including: objective and rationale for using multiple data sources; methods used to manage, analyse and (where applicable) combine data; and approaches used to assess and report heterogeneity between data sources.DesignA systematic review of published studies.Data sourcesPubmed and Embase databases were searched using list of named primary care EHR databases; supplementary hand searches of reference list of studies were retained after initial screening.Study selectionObservational studies published between January 2000 and May 2018 were selected, which included at least two different primary care EHR databases.Results6054 studies were identified from database and hand searches, and 109 were included in the final review, the majority published between 2014 and 2018. Included studies used 38 different primary care EHR data sources. Forty-seven studies (44%) were descriptive or methodological. Of 62 analytical studies, 22 (36%) presented separate results from each database, with no attempt to combine them; 29 (48%) combined individual patient data in a one-stage meta-analysis and 21 (34%) combined estimates from each database using two-stage meta-analysis. Discussion and exploration of heterogeneity was inconsistent across studies.ConclusionsComparing patterns and trends in different populations, or in different primary care EHR databases from the same populations, is important and a common objective for multi-database studies. When combining results from several databases using meta-analysis, provision of separate results from each database is helpful for interpretation. We found that these were often missing, particularly for studies using one-stage approaches, which also often lacked details of any statistical adjustment for heterogeneity and/or clustering. For two-stage meta-analysis, a clear rationale should be provided for choice of fixed effect and/or random effects or other models.

scholarly journals Characterization and selection of Japanese electronic health record databases used as data sources for non-interventional observational studies

2021 ◽  
Author(s):  
Yumi Wakabayashi ◽  
Masamitsu Eitoku ◽  
Narufumi Suganuma
Keyword(s):  
Electronic Health Record ◽  
Observational Studies ◽  
Large Scale ◽  
Data Sources ◽  
Flow Diagram ◽  
Health Record ◽  
Medical Institutions ◽  
Data Source ◽  
Electronic Health ◽  
Using Data

Abstract Background Interventional studies are the fundamental method for obtaining answers to clinical question. However, these studies are sometimes difficult to conduct because of insufficient financial or human resources or the rarity of the disease in question. One means of addressing these issues is to conduct a non-interventional observational study using electronic health record (EHR) databases as the data source, although how best to evaluate the suitability of an EHR database when planning a study remains to be clarified. The aim of the present study is to identify and characterize the data sources that have been used for conducting non-interventional observational studies in Japan and propose a flow diagram to help researchers determine the most appropriate EHR database for their study goals. Methods We compiled a list of published articles reporting observational studies conducted in Japan by searching PubMed for relevant articles published in the last 3 years and by searching database providers’ publication lists related to studies using their databases. For each article, we reviewed the abstract and/or full text to obtain information about data source, target disease or therapeutic area, number of patients, and study design (prospective or retrospective). We then characterized the identified EHR databases. Results In Japan, non-interventional observational studies have been mostly conducted using data stored locally at individual medical institutions (713/1463) or collected from several collaborating medical institutions (351/1463). Whereas the studies conducted with large-scale integrated databases (195/1463) were mostly retrospective (68.2%), 27.2% of the single-center studies, 46.2% of the multi-center studies, and 74.4% of the post-marketing surveillance studies, identified in the present study, were conducted prospectively. Conclusions Our analysis revealed that the non-interventional observational studies were conducted using data stored local at individual medical institutions or collected from collaborating medical institutions in Japan. Disease registries, disease databases, and large-scale databases would enable researchers to conduct studies with large sample sizes to provide robust data from which strong inferences could be drawn. Using our flow diagram, researchers planning non-interventional observational studies should consider the strengths and limitations of each available database and choose the most appropriate one for their study goals. Trial registration Not applicable.

scholarly journals Formal representation of patients’ care context data: the path to improving the electronic health record

2020 ◽  
Vol 27 (11) ◽  
pp. 1648-1657
Author(s):  
Tiago K Colicchio ◽  
Pavithra I Dissanayake ◽  
James J Cimino
Keyword(s):  
Electronic Health Record ◽  
Data Entry ◽  
Data Sources ◽  
Health Record ◽  
Formal Representation ◽  
Semantic Relationships ◽  
Navigation Data ◽  
Multiple Data ◽  
Context Data ◽  
Electronic Health

Abstract Objective To develop a collection of concept-relationship-concept tuples to formally represent patients’ care context data to inform electronic health record (EHR) development. Materials and Methods We reviewed semantic relationships reported in the literature and developed a manual annotation schema. We used the initial schema to annotate sentences extracted from narrative note sections of cardiology, urology, and ear, nose, and throat (ENT) notes. We audio recorded ENT visits and annotated their parsed transcripts. We combined the results of each annotation into a consolidated set of concept-relationship-concept tuples. We then compared the tuples used within and across the multiple data sources. Results We annotated a total of 626 sentences. Starting with 8 relationships from the literature, we annotated 182 sentences from 8 inpatient consult notes (initial set of tuples = 43). Next, we annotated 232 sentences from 10 outpatient visit notes (enhanced set of tuples = 75). Then, we annotated 212 sentences from transcripts of 5 outpatient visits (final set of tuples = 82). The tuples from the visit transcripts covered 103 (74%) concepts documented in the notes of their respective visits. There were 20 (24%) tuples used across all data sources, 10 (12%) used only in inpatient notes, 15 (18%) used only in visit notes, and 7 (9%) used only in the visit transcripts. Conclusions We produced a robust set of 82 tuples useful to represent patients’ care context data. We propose several applications of our tuples to improve EHR navigation, data entry, learning health systems, and decision support.

scholarly journals Measuring the prevalence of 60 health conditions in older Australians in residential aged care with electronic health records: a retrospective dynamic cohort study

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Kimberly E. Lind ◽  
Magdalena Z. Raban ◽  
Lindsey Brett ◽  
Mikaela L. Jorgensen ◽  
Andrew Georgiou ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Health Status ◽  
Electronic Health Record ◽  
Quality Care ◽  
Aged Care ◽  
Data Sources ◽  
Health Conditions ◽  
Residential Aged Care ◽  
Health Record ◽  
Electronic Health

Abstract Background The number of older Australians using aged care services is increasing, yet there is an absence of reliable data on their health. Multimorbidity in this population has not been well described. A clear picture of the health status of people using aged care is essential for informing health practice and policy to support evidence-based, equitable, high-quality care. Our objective was to describe the health status of older Australians living in residential aged care facilities (RACFs) and develop a model for monitoring health conditions using data from electronic health record systems. Methods Using a dynamic retrospective cohort of 9436 RACF residents living in 68 RACFs in New South Wales and the Australian Capital Territory from 2014 to 2017, we developed an algorithm to identify residents’ conditions using aged care funding assessments, medications administered, and clinical notes from their facility electronic health record (EHR). We generated age- and sex-specific prevalence estimates for 60 health conditions. Agreement between conditions recorded in aged care funding assessments and those documented in residents’ EHRs was evaluated using Cohen’s kappa. Cluster analysis was used to describe combinations of health conditions (multimorbidity) occurring among residents. Results Using all data sources, 93% of residents had some form of circulatory disease, with hypertension the most common (62%). Most residents (93%) had a mental or behavioural disorder, including dementia (58%) or depression (54%). For most conditions, EHR data identified approximately twice the number of people with the condition compared to aged care funding assessments. Agreement between data sources was highest for multiple sclerosis, Huntington’s disease, and dementia. The cluster analysis identified seven groups with distinct combinations of health conditions and demographic characteristics and found that the most complex cluster represented a group of residents that had on average the longest lengths of stay in residential care. Conclusions The prevalence of many health conditions among RACF residents in Australia is underestimated in previous reports. Aged care EHR data have the potential to be used to better understand the complex health needs of this vulnerable population and can help fill the information gaps needed for population health surveillance and quality monitoring.

scholarly journals Building a high quality medical data architecture for multiple uses in an integrated health care environment

2014 ◽  
Vol 3 (5) ◽  
pp. 55 ◽  
Author(s):  
Frank Boterenbrood ◽  
Irene Krediet ◽  
William Goossen
Keyword(s):  
Electronic Health Record ◽  
Data Exchange ◽  
Research Question ◽  
Data Communication ◽  
Medical Data ◽  
Health Record ◽  
Electronic Health Record Data ◽  
Clinical Models ◽  
Multiple Uses ◽  
Electronic Health

Objective: The aim was to create a reliable information provisioning system in healthcare for both care and research processes, based on existing data standards and standardized electronic messages. The research question is: How can a Clinical Data Ware House (CDWH) be developed for standardized basic patient data, generic nursing data and data about oncology nursing, allowing management of Electronic Health Record data, electronic data exchange and data analytics? Materials and methods: The main instrument used was the Detailed Clinical Model (DCM) data standardization approach. Further, data communication utilized HealthLevel7v3 (HL7v3) messages, transported by Mirth Connect. In an incremental, design-oriented research project, CDWH-prototypes were constructed using Enterprise Architect, a HL7v3 generator plug-in, SQL Server technology and PostgreSQL-based CDWH-technology. Results: The project resulted in 16 existing DCMs selected and 6 new DCMs defined. From those DCMs, a HL7v3 message structure was generated and a CDWH created. Implementing specialized Data Marts (DM) a connection between the CDWH and one Electronic Health Record system was built. Discussion: Detailed Clinical Models improve data quality, yet building them consumes time and resources. Some required data codes could not be identified in time and dummy codes were used instead. The existence of unstructured medical data in legacy systems may proof to be an obstacle in the future. Conclusion: The project shows that using Detailed Clinical Models as the sole source for system development leads to a sound design for a CDWH and HL7v3 messages, supporting a standards based health information system, suitable for multiple uses.

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.

scholarly journals Measuring the prevalence of 60 health conditions in older Australians in residential aged care with electronic health records: a retrospective dynamic cohort study

2020 ◽  
Author(s):  
Kimberly E. Lind ◽  
Magdalena Z. Raban ◽  
Lindsey Brett ◽  
Mikaela L. Jorgensen ◽  
Andrew Georgiou ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Health Status ◽  
Electronic Health Record ◽  
Quality Care ◽  
Aged Care ◽  
Data Sources ◽  
Health Conditions ◽  
Residential Aged Care ◽  
Health Record ◽  
Electronic Health

Abstract Background: The number of older Australians using aged care services is increasing, yet there is an absence of reliable data on their health. Multimorbidity in this population has not been well described. A clear picture of the health status of people using aged care is essential for informing health practice and policy to support evidence-based, equitable, high-quality care. Our objective was to describe the health status of older Australians living in residential aged care facilities (RACFs) and develop a model for monitoring health conditions using data from electronic health record systems. Methods: Using a dynamic retrospective cohort of 9436 RACF residents living in 68 RACFs in New South Wales and the Australian Capital Territory from 2014-2017, we developed an algorithm to identify residents’ conditions using: aged care funding assessments; medications administered; and clinical notes from their facility electronic health record (EHR). We generated age and sex-specific prevalence estimates for 60 health conditions. Agreement between conditions recorded in aged care funding assessments and those documented in residents’ EHRs was evaluated using Cohen’s Kappa. Cluster analysis was used to describe combinations of health conditions (multimorbidity) occurring among residents.Results: Using all data sources, 93% of residents had some form of circulatory disease, with hypertension the most common (62%). Most residents (93%) had a mental or behavioural disorder, including dementia (58%) or depression (54%). For most conditions, EHR data identified approximately twice the number of people with the condition compared to aged care funding assessments. Agreement between data sources was highest for multiple sclerosis, Huntington’s disease and dementia. The cluster analysis identified seven groups with distinct combinations of health conditions and demographic characteristics and found that the most complex cluster represented a group of residents that had on average the longest lengths of stay in residential care.Conclusions: The prevalence of many health conditions among RACF residents in Australia is underestimated in previous reports. Aged care EHR data have the potential to be used to better understand the complex health needs of this vulnerable population and can help fill the information gaps needed for population health surveillance and quality monitoring.

scholarly journals Clinical trial site identification practices and the use of electronic health records in feasibility evaluations: An interview study in the Nordic countries

2021 ◽  
pp. 174077452110385
Author(s):  
Niina Laaksonen ◽  
Mia Bengtström ◽  
Anna Axelin ◽  
Juuso Blomster ◽  
Mika Scheinin ◽  
...  
Keyword(s):  
Electronic Health Record ◽  
Data Sources ◽  
Pharmaceutical Companies ◽  
Health Record ◽  
Electronic Health Record Data ◽  
Trial Site ◽  
Record Data ◽  
Electronic Health ◽  
Site Identification ◽  
Trial Participants

Introduction: Feasibility evaluations are performed to create the best possible starting point for the set-up and execution of a clinical trial, and to identify any obstacles for successful trial conduct. New digital technologies can provide various types of data for use in feasibility evaluations. There is a need to identify and compare such data sources for trial site identification and for evaluating the sites’ patient recruitment potential. Especially, information is needed on the use of electronic health records. We investigated how different data sources are used by pharmaceutical companies operating in the Nordic countries for identifying trial sites and for evaluating their potential to recruit trial participants. Methods: This was a semi-structured qualitative interview study with 21 participants from pharmaceutical companies and contract research organizations operating in Finland, Sweden, Denmark and Norway. Qualitative content analysis was applied. Results: For identifying countries and trial sites on a global level, the trial sponsors mostly used databases on previous trial performance. The use of electronic health record data was very limited. Sites’ and investigators’ visibility in various databases was seen as fundamental for their countries becoming selected into new clinical trials. For estimating the sites’ recruitment projections, most sites were seen to base their patient count estimates solely on their previous experience. Some sites had reviewed their electronic health record data, which was considered to increase the accuracy of their recruitment estimates and these sites’ attractivity. Along with dialogs with investigators, the sponsors used various data sources to validate the investigators’ estimates. Legislative obstacles were seen to hinder the use of electronic health record queries for estimation of patient counts. Conclusion: Visibility in the databases used by trial sponsors is crucial for the countries and sites to be identified. Site selection appears to be based on trust and relationships built from experience, but electronic data provide the support upon which the trust is based. Estimation of the number of potential trial participants is a complex and time-consuming process for both investigators and sponsors. Sponsors seem to favour sites who could support their patient count estimates with electronic health record data as they were quicker in providing the estimates and more reliable than sites with no electronic health record evidence. The patient count evaluation process could be simplified, accelerated and made more reliable with more systematic use of electronic health record evidence in the feasibility evaluation phase. This would increase the accuracy of the patient count estimates and, on its part, contribute to improved recruitment success.

scholarly journals Characterization and selection of Japanese electronic health record databases used as data sources for non-interventional observational studies

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yumi Wakabayashi ◽  
Masamitsu Eitoku ◽  
Narufumi Suganuma
Keyword(s):  
Electronic Health Record ◽  
Observational Studies ◽  
Large Scale ◽  
Data Sources ◽  
Flow Diagram ◽  
Health Record ◽  
Medical Institutions ◽  
Data Source ◽  
Electronic Health ◽  
Using Data

Abstract Background Interventional studies are the fundamental method for obtaining answers to clinical questions. However, these studies are sometimes difficult to conduct because of insufficient financial or human resources or the rarity of the disease in question. One means of addressing these issues is to conduct a non-interventional observational study using electronic health record (EHR) databases as the data source, although how best to evaluate the suitability of an EHR database when planning a study remains to be clarified. The aim of the present study is to identify and characterize the data sources that have been used for conducting non-interventional observational studies in Japan and propose a flow diagram to help researchers determine the most appropriate EHR database for their study goals. Methods We compiled a list of published articles reporting observational studies conducted in Japan by searching PubMed for relevant articles published in the last 3 years and by searching database providers’ publication lists related to studies using their databases. For each article, we reviewed the abstract and/or full text to obtain information about data source, target disease or therapeutic area, number of patients, and study design (prospective or retrospective). We then characterized the identified EHR databases. Results In Japan, non-interventional observational studies have been mostly conducted using data stored locally at individual medical institutions (663/1511) or collected from several collaborating medical institutions (315/1511). Whereas the studies conducted with large-scale integrated databases (330/1511) were mostly retrospective (73.6%), 27.5% of the single-center studies, 47.6% of the multi-center studies, and 73.7% of the post-marketing surveillance studies, identified in the present study, were conducted prospectively. We used our findings to develop an assessment flow diagram to assist researchers in evaluating and choosing the most suitable EHR database for their study goals. Conclusions Our analysis revealed that the non-interventional observational studies were conducted using data stored local at individual medical institutions or collected from collaborating medical institutions in Japan. Disease registries, disease databases, and large-scale databases would enable researchers to conduct studies with large sample sizes to provide robust data from which strong inferences could be drawn.

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