353 A new era of data extraction: Example of automated extraction PSA values from electronic health records

2016 ◽  
Vol 15 (3) ◽  
pp. e353
Author(s):  
S-R. Leyh-Bannurah ◽  
P. Dell'Oglio ◽  
Z. Tian ◽  
M. Graefen ◽  
H. Huland ◽  
...  
Medical Care ◽  
2017 ◽  
Vol 55 (10) ◽  
pp. e73-e80 ◽  
Author(s):  
Zhe Tian ◽  
Simon Sun ◽  
Tewodros Eguale ◽  
Christian M. Rochefort

2018 ◽  
Vol 71 (11) ◽  
pp. A2031
Author(s):  
Adelaide Maria Arruda-Olson ◽  
Naveed Afzal ◽  
Vishnu Priya Mallipeddi ◽  
Ahmad Said ◽  
Homam Moussa Pacha ◽  
...  

2018 ◽  
Vol 17 (2) ◽  
pp. e1209
Author(s):  
S.-R. Leyh-Bannurah ◽  
Z. Tian ◽  
P.I. Karakiewicz ◽  
U. Wolffgang ◽  
D. Pehrke ◽  
...  

2019 ◽  
Vol 26 (11) ◽  
pp. 1389-1400
Author(s):  
Natalie Wiebe ◽  
Lucia Otero Varela ◽  
Daniel J Niven ◽  
Paul E Ronksley ◽  
Nicolas Iragorri ◽  
...  

Abstract Objective Despite the widespread and increasing use of electronic health records (EHRs), the quality of EHRs is problematic. Efforts have been made to address reasons for poor EHR documentation quality. Previous systematic reviews have assessed intervention effectiveness within the outpatient setting or paper documentation. The purpose of this systematic review was to assess the effectiveness of interventions seeking to improve EHR documentation within an inpatient setting. Materials and Methods A search strategy was developed based on elaborated inclusion/exclusion criteria. Four databases, gray literature, and reference lists were searched. A REDCap data capture form was used for data extraction, and study quality was assessed using a customized tool. Data were analyzed and synthesized in a narrative, semiquantitative manner. Results Twenty-four studies were included in this systematic review. Owing to high heterogeneity, quantitative comparison was not possible. However, statistically significant results in interventions and affected outcomes were analyzed and discussed. Education and implementation of a new EHR reporting system were the most successful interventions, as evidenced by significantly improved EHR documentation. Discussion Heterogeneity of interventions, outcomes, document type, EHR user, and other variables led to difficulty in measuring EHR documentation quality and effectiveness of interventions. However, the use of education as a primary intervention aligned closely with existing literature in similar fields. Conclusions Interventions implemented to enhance EHR documentation are highly variable and require standardization. Emphasis should be placed on this novel area of research to improve communication between healthcare providers and facilitate data sharing between centers and countries. PROSPERO Registration Number: CRD42017083494.


2021 ◽  
Author(s):  
Lamorna Brown ◽  
Frank Sullivan ◽  
Tom Kelsey ◽  
Utkarsh Agrawal

Abstract Background: Lung cancer is one of the most common and aggressive forms of cancer, resulting in a low survival and high mortality rate. To improve cancer related outcomes, high-risk subpopulations should be identified to reduce overdiagnosis of lung cancer and aid in the implementation of interventions. Electronic Health Records (EHRs) have been effective in identifying cohorts and phenotyping diseases. To identify whether EHR data can be used in risk modelling for lung cancer, this review will seek to identify data features that are contained in EHRs and related to lung cancer. Methods: A search strategy was developed and then applied to MEDLINE via Ovid, Web of Science, Scopus and the Cochrane library. The titles and abstracts of studies will be identified and screened independently by reviewers. Reviewers will read the full texts of studies that appear to meet the eligibility criteria after initial screening. Articles that meet the criteria at this stage, will have their bibliographies examined for relevant studies. Data extraction will then be performed independently by reviewers and a narrative synthesis will be carried out.Discussion: While risk factors for lung cancer have been extensively researched, there has to date been no effort to identify whether information that relates to these factors are available in EHRs and can be modelled with. As such, the results of the review will seek to broaden knowledge around the use of EHRs in lung cancer risk modelling and inform researchers of the variables that are available in EHRs.Registration: PROSPERO CRD42021246781, Registered on 26/04/21.


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